The Levers of HIV Model (1.0.1)

Chicago’s demographic, neighborhood, sex risk behaviors, sexual network data, and HIV prevention and treatment cascade information from 2015 were integrated as input to a new agent-based model (ABM) called the Levers-of-HIV-Model (LHM). This LHM, written in NetLogo, forms patterns of sexual relations among Men who have Sex with Men (MSM) based on static traits (race/ethnicity, and age) and dynamic states (sexual relations and practices) that are found in Chicago. LHM’s five modules simulate and count new infections at the two marker years of 2023 and 2030 for a wide range of distinct scenarios or levers, in which the levels of PrEP and ART linkage to care, retention, and adherence or viral load are increased over time from the 2015 baseline levels.

Release Notes

First version of a public release to accompany a publication

Associated Publications

https://doi.org/10.1371/journal.pone.0274288

Shellmound Trade (1.0.0)

This model simulates different trade dynamics in shellmound (sambaqui) builder communities in coastal Southern Brazil. It features two simulation scenarios, one in which every site is the same and another one testing different rates of cooperation. The purpose of the model is to analyze the networks created by the trade dynamics and explore the different ways in which sambaqui communities were articulated in the past.

How it Works? There are a few rules operating in this model. In either mode of simulation, each tick the agents will produce an amount of resources based on the suitability of the patches inside their occupation-radius, after that the procedures depend on the trade dynamic selected. For BRN? the agents will then repay their owed resources, update their reputation value and then trade again if they need to. For GRN? the agents will just trade with a connected agent if they need to. After that the agents will then consume a random amount of resources that they own and based on that they will grow (split) into a new site or be removed from the simulation. The simulation runs for 1000 ticks. Each patch correspond to a 300x300m square of land in the southern coast of Santa Catarina State in Brazil. Each agent represents a shellmound (sambaqui) builder community. The data for the world were made from a SRTM raster image (1 arc-second) in ArcMap. The sites can be exported into a shapefile (.shp) vector to display in ArcMap. It uses a UTM Sirgas 2000 22S projection system.

Release Notes

Reviewed version after thesis defense.

Associated Publications

https://doi.org/10.11606/T.71.2023.tde-18012024-102858

Title: Implementation of a complex agent-based model to address the effects of interacting ecological stressors and alternative management strategies on an endangered species

Institution: Purdue University, Department of Forestry and Natural Resources

Location: Purdue University West Lafayette, IN is preferred. However, we will consider hybrid and remote work models.

Job Category: Post-Doctoral Scholar

Salary: Commensurate with standards for post-doctoral scholars in the Department of Forestry and Natural Resources at Purdue University the starting salary will be at least $47,500 annually for the first year with opportunities for raises during subsequent project years. The position includes benefits typical for post-doctoral scholars at Purdue (https://www.purdue.edu/gradschool/postdoctoral-studies/resources/index.php).

Duration of Appointment: Applicant will be hired for a minimum of one year. Funding is available to support a post-doctoral scholar for the four-year duration of this project pending approval of additional funds after the completion of the first two project years. Pertinent Websites: https://serdp-estcp.org/projects/details/89fdcf5b-0c44-41f9-af97-fd1d45908863/rc22-3216-project-overview and https://www.purdue.edu/fnr/sites/zollner/

Start Date: As Soon As Possible.

Project Description: The federally endangered Least Bell’s Vireo (LBVI, Vireo bellii pusillus) nests in narrow riparian areas surrounded by the heavily urbanized matrix of Southern California. Several of the largest remaining patches of LBVI nesting habitat occur on US Department of Defense (DoD) military installations and in US Army Corps of Engineers (USACE) flood control basins. Expenses for ESA compliance related to LBVI are among the highest of all listed bird species, with widespread operational and financial impacts on federal action agencies and military installations. A complex array of threats and stressors interact to threaten LBVI populations, including groundwater extraction, loss of streamflow inputs due to water recycling programs, changing flood and fire regimes, nest parasitism by brown-headed cowbirds (Molothrus ater), and negative impacts to riparian vegetation from invasive non-native plants and insects. One challenge in developing management strategies for recovery is understanding how different stressors may interact, particularly with emerging threats like new invasive species or major changes in disturbance regimes due to climate change. A ~25-minute video describing this project in more detail can be viewed at this link (https://youtu.be/c0DQPcSk-Qg). The goal of this research project is to develop an individual/agent-based modeling tool that integrates sub-models reflecting different stressors, and synthesizes those sub-models to understand the relative effectiveness of a range of PI- and stakeholder-generated management scenarios.

Position Description/Project Role: The selected post-doctoral scholar will work closely with PhD students in the labs of Dr. Pat Zollner and Dr. Jeff Holland as well as with all project Co-PIs (see below) throughout the model development cycle to design, document, implement in code, and analyze outputs from a complex agent-based model. Specifically, successful applicants will have the following skills and experience:

1) Collaborative design and development (in code) of an agent-based model that will integrate sub-models developed by multiple collaborators on the project team. The ability to plan for this integration, maintain a code base, and help collaborators develop models that will fit seamlessly into a global model will be critical;

2) Ability to run agent-based modeling software at scale, so that a complex model with thousands of interacting agents can be run hundreds, if not thousands, of times for different analyses working on a computing cluster and/or using cloud-based resources. This skill is required for model testing, calibration, sensitivity analysis, and applied analyses to simulate many stakeholder or researcher-driven alternative management scenarios to assess their relative effectiveness; and

3) Strong code documentation skills (e.g., modeling notebooks, comments in code) will be required, as well as the commitment to work with all on the project team to follow documentation formats specific to agent-based models (ODD, TRACE). This is a unique opportunity for individuals interested in the interface of individual/agent-based modeling and quantitative wildlife conservation. The position provides relevant experience for a career trajectory within a government agency or a research career at a university or NGO. The post-doctoral scholar will be supervised by Dr. Patrick Zollner (Purdue University Department of Forestry and Natural Resources). They will collaborate with; Dr. Richard Fischer from the US Army Engineer Research and Development Center, Mr. Casey Lott Conservation Science and Data Visualization, LLC, Dr. Jeffrey Holland Purdue University Department of Entomology, and Ms. Melissa Rohde of Rohde Environmental Consulting LLC.

Specific Duties: The post-doctoral scholar will serve as the hub coordinating the design and code compatibility of sub-models from all project collaborators. They will play a critical role in designing and coding the overarching model that integrates sub-models related to different stressors as well simulation experiments that investigate the interactive effects of those stressors and their implications for management activities. Responsibility for specific tasks will be assigned on a case-by-case basis and the post-doctoral scholar will work closely with the PhD students and project Co-PIs on all aspects of this project.

How to Apply: Interested applicants should compile all of the following materials into a single pdf file; a CV that includes contact information for three professional references, a 1-page statement of interest, and responses to the following 5 questions (each of these responses should be 250 words or less).

1. Describe a situation that demonstrates your work ethic and ability to complete complex tasks in a timely manner.
2. Provide an example of a work/academic situation that typifies how you handle adversity when striving to attain a goal.
3. What motivates you to pursue post-doctoral scholarship, and how will participation in this project prepare you to achieve your career goals?
4. Please describe a specific example from your work/academic experience that demonstrates your curiosity and creativity.
5. What are your strengths and weaknesses with regard to achieving goals individually and in collaboration with others?

That single pdf should be attached to an email that has a subject line of “Application for Post-Doctoral Scholar on Least Bell’s Vireo ABM”. That email should be sent to Dr. Patrick Zollner ([email protected]) and applicants should understand that their application materials may be reviewed by other project collaborators as part of application evaluation. Application review will begin on January 16 of 2023 and continue until a suitable applicant is hired for the position.

Qualifications: PhD in Computer Programming, Software Engineering, or a related field with an interest in conservation of endangered species. Alternatively, PhD in Ecological Modelling, Wildlife Biology or a related discipline with experience in Agent Based Modeling.

When preparing materials (statement of interest & response to 5 questions) applicants should explicitly address their demonstrated organizational skills, interest/background in individual/agent-based modeling, quantitative skills, and their ability to mentor others. Applicants should be highly motivated with a demonstrated ability to work independently and collaboratively. The post-doctoral scholar that we hire should be able to readily interact with partners including government agencies across many levels as well as non-governmental organizations. Applicants with experience publishing peer-reviewed journal articles, a strong work ethic, demonstrated technical writing ability, training in ecological modeling, excellent interpersonal skills, demonstrated skill or skill potential in quantitative ecology and proficiency in R will be most competitive. Experience developing individual/agent-based models in NetLogo or equivalent platforms, knowledge related to optimizing solutions to network structure challenges, familiarity with conservation challenges faced by LBVI, as well as candidates who bring unique contributions to the diverse perspectives within the Department of Forestry and Natural Resources are all additional elements that will make applicants more competitive.

Purdue is a land-grant university of over 40,000 students and ranked the 10th best public university in the U.S. The Department of Forestry and Natural Resources is housed administratively in the College of Agriculture (#7 US ranking) and offers vibrant, nationally ranked graduate programs in wildlife and ecology. Located in West Lafayette, Indiana, Purdue is an easy drive from Indianapolis and Chicago. The West Lafayette-Lafayette area is home to a diverse community of 174,000, with good schools, safe neighborhoods, over 40 parks and extensive trail systems, active Farmers Markets, and year-long community festivals and art events.

Contact Persons: Dr. Patrick Zollner Contact Phones: (765) 430-7858 Contact e-mails: [email protected]

The Levers of HIV Model (1.0.2)

Chicago’s demographic, neighborhood, sex risk behaviors, sexual network data, and HIV prevention and treatment cascade information from 2015 were integrated as input to a new agent-based model (ABM) called the Levers-of-HIV-Model (LHM). This LHM, written in NetLogo, forms patterns of sexual relations among Men who have Sex with Men (MSM) based on static traits (race/ethnicity, and age) and dynamic states (sexual relations and practices) that are found in Chicago. LHM’s five modules simulate and count new infections at the two marker years of 2023 and 2030 for a wide range of distinct scenarios or levers, in which the levels of PrEP and ART linkage to care, retention, and adherence or viral load are increased over time from the 2015 baseline levels.

Release Notes

First version of a public release to accompany a publication

Associated Publications

https://doi.org/10.1371/journal.pone.0274288

SIM-VOLATILE: Adoption of emerging circular technologies in the waste-treatment sector (1.0.0)

The SIM-VOLATILE model is a technology adoption model at the population level. The technology, in this model, is called Volatile Fatty Acid Platform (VFAP) and it is in the frame of the circular economy. The technology is considered an emerging technology and it is in the optimization phase. Through the adoption of VFAP, waste-treatment plants will be able to convert organic waste into high-end products rather than focusing on the production of biogas. Moreover, there are three adoption/investment scenarios as the technology enables the production of polyhydroxyalkanoates (PHA), single-cell oils (SCO), and polyunsaturated fatty acids (PUFA). However, due to differences in the processing related to the products, waste-treatment plants need to choose one adoption scenario.

In this simulation, there are several parameters and variables. Agents are heterogeneous waste-treatment plants that face the problem of circular economy technology adoption. Since the technology is emerging, the adoption decision is associated with high risks. In this regard, first, agents evaluate the economic feasibility of the emerging technology for each product (investment scenarios). Second, they will check on the trend of adoption in their social environment (i.e. local pressure for each scenario). Third, they combine these two economic and social assessments with an environmental assessment which is their environmental decision-value (i.e. their status on green technology). This combination gives the agent an overall adaptability fitness value (detailed for each scenario). If this value is above a certain threshold, agents may decide to adopt the emerging technology, which is ultimately depending on their predominant adoption probabilities and market gaps.

Release Notes

A detailed description of the model is provided in an ODD document attached. The instruction on how to run the model, are provided under the info-tab in the Netlogo interface.

Associated Publications

Farahbakhsh, Siavash, Stien Snellinx, Anouk Mertens, Edward Belderbos, Liselot Bourgeois, and Jef Van Meensel. “What’s stopping the waste-treatment industry from adopting emerging circular technologies? An agent-based model revealing drivers and barriers.” Resources, Conservation and Recycling 190 (2023): 106792. https://doi.org/10.1016/j.resconrec.2022.106792.

F Velghe, F De Wilde, S Snellinx, S Farahbakhsh, E Belderbos, C Peral, A Wiedemann, S Hiessl, J Michels, M-A Pierrard, T Dietrich, Volatile fatty acid platform – a cornerstone for the circular bioeconomy, FEMS Microbiology Letters, Volume 368, Issue 9, May 2021, fnab056, https://doi.org/10.1093/femsle/fnab056

Benchmark for DMASON (1.0.0)

Agent-based modeling and simulation (ABMS) is a class of computational models for simulating the actions and interactions of autonomous agents with the goal of assessing their effects on a system as a whole. Several frameworks for generating parallel ABMS applications have been developed taking advantage of their common characteristics, but there is a lack of a general benchmark for comparing the performance of generated applications. We propose and design a benchmark that takes into consideration the most common characteristics of this type of applications and includes parameters for influencing their relevant performance aspects. We provide an initial implementation of the benchmark for DMASON parallel ABMS platform, and we use it for comparing the applications generated by these platforms.

Release Notes

First release of Benchmark for DMASON

Associated Publications

https://doi.org/10.1016/j.simpat.2023.102812 https://doi.org/10.1007/s11227-018-2688-8

An agent-based model of scapegoating (1.0.0)

This agent-based model investigates scapegoating as a social mechanism of crisis management. Inspired by René Girard’s mimetic theory, it simulates how individual tension accumulates and spreads across a small-world network. When tension exceeds certain thresholds, leaders emerge and accuse marginalized agents, who may attempt to transfer blame to substitutes. If scapegoating occurs, collective tension decreases, but victims become isolated while leaders consolidate temporary authority. This simulation provides a conceptual and methodological framework for exploring how collective blame, crisis contagion, and leadership paradoxes emerge in complex networks. It can also be extended with empirical data, such as social media dynamics of online harassment and virtual lynching, offering potential applications for both theoretical research and practical crisis monitoring.

Release Notes

Version 1.0 of the Scapegoating ABM. This release provides the complete NetLogo model, comprehensive ODD protocol documentation, and illustrative configurations for reproducing core dynamics such as tension propagation, leader emergence, and scapegoat selection. The release is intended for researchers interested in network science, collective behavior, and mimetic theory, and serves as the basis for future empirical validation with social media datasets.

Associated Publications

An integrated socio-economic Agent-Based Modeling framework towards assessing farmers’ decision making under water scarcity and varying utility function (1.0.0)

A spatio-temporal Agent Based Modeling (ABM) framework is developed to probabilistically predict farmers’ decisions in the context of climate-induced water scarcity under varying utility optimization functions. The proposed framework forecasts farmers’ behavior assuming varying utility functions. The framework allows decision makers to forecast the behavior of farmers through a user-friendly platform with clear output visualization. The functionality of the proposed ABM is illustrated in an agriculturally dominated plain along the Eastern Mediterranean coastline.

Study area GIS data available upon request to [email protected]

Release Notes

Enter the number of proposed farms and the characteristics xls file. Click on the SETUP button to set up the model. Click on GO.

Associated Publications

ThomondSim (1.0.0)

ThomondSim is a simulation of the political and economic landscape of the medieval kingdom of Thomond, southwestern Ireland, between 1276 and 1318.

Its goal is to analyze how deteriorating environmental and economic conditions caused by the Little Ice Age (LIA), the Great European Famine of 1315-1322, and wars between England and Scotland affected the outcomes of a local war involving Gaelic and English aristocratic lineages. This ABM attempts to model both the effects of devastation on the human environment and the modus operandi of late-medieval war and diplomacy.

The model is the digital counterpart of the science discovery board game The Triumphs of Turlough. Its procedures closely correspond to the game’s mechanics, to the point that ToT can be considered an interactive, analog version of this ABM.

Release Notes

This model was created using NetLogo 6.2.2.

It runs on an invisible network environment overlayed on a static map. You do not need the map if you simply want to use the model to run experiments. However, if you wish to use it for educational purposes, you might wish to download.

To do so, click on File > Import > Import Patch Colors RGB, then select the file Map_ThomondSim.png (available on this page), wherever you have saved it.

On the “tools” tab, click on Turtle Shape Editor > Import from Library. You’ll see a list with icons. Select the following icons and click “import”: chess bishop, chess king, chess knight, and crown

2 -Save the file ThomondSimMap.png on your computer

3- Open NetLogo. On the “tools” tab, click on Turtle Shape Editor > Import from Library. You’ll see a list with icons. Select the following icons and click “import”: chess bishop, chess king, chess knight, and crown

4- Open ThomondSim.nlogo

Associated Publications

WEEM (Woodlot Establishment and Expansion Model) (1.0.0)

The agent-based model WEEM (Woodlot Establishment and Expansion Model) as described in the journal article, has been designed to make use of household socio-demographics (household status, birth, and death events of households), to better understand the temporal dynamics of woodlot in the buffer zones of Budongo protected forest reserve, Masindi district, Uganda. The results contribute to a mechanistic understanding of what determines the current gap between intention and actual behavior in forest land restoration at farm level.

Release Notes

First version of the WEEM model, which simulates the household decision making behavior through number of established woodlots. The model builds on the assumption of theory of planned behavior focusing on household intention and actual behavior in woodlot establishment.

Associated Publications

Ahimbisibwe et al 2021. Understanding Smallholder Farmer Decision Making in Forest Land Restoration Using Agent-Based Modeling, submitted for publication in SESMO.

The Levers of HIV Model (1.0.0)

Chicago’s demographic, neighborhood, sex risk behaviors, sexual network data, and HIV prevention and treatment cascade information from 2015 were integrated as input to a new agent-based model (ABM) called the Levers-of-HIV-Model (LHM). This LHM, written in NetLogo, forms patterns of sexual relations among Men who have Sex with Men (MSM) based on static traits (race/ethnicity, and age) and dynamic states (sexual relations and practices) that are found in Chicago. LHM’s five modules simulate and count new infections at the two marker years of 2023 and 2030 for a wide range of distinct scenarios or levers, in which the levels of PrEP and ART linkage to care, retention, and adherence or viral load are increased over time from the 2015 baseline levels.

Release Notes

First version of a public release to accompany a publication

Associated Publications

https://doi.org/10.1371/journal.pone.0274288

Title: Agent Based Modeling to Improve Cage-Free Housing Systems: What Does the Hen See?

Institution: Purdue University, Department of Forestry and Natural Resources

Location: Purdue University West Lafayette, IN is preferred. However, we will consider hybrid and remote work models.

Job Category: Post-Doctoral Scholar

Salary: Commensurate with standards for post-doctoral scholars in the Department of Forestry and Natural Resources at Purdue University the starting annual salary will be at least $47,500. The position includes benefits typical for post-doctoral scholars at Purdue (https://www.purdue.edu/gradschool/postdoctoral-studies/resources/index.php).

Duration of Appointment: Eighteen months.

Pertinent Websites: https://ag.purdue.edu/stories/through-the-hens-eyes-1-million-grant-to-improve-cage-free-housing-for-egg-laying/ and https://cris.nifa.usda.gov/cgi-bin/starfinder/0?path=fastlink1.txt&id=anon&pass=&search=R=95189&format=WEBFMT6NT Start Date: Negotiable but desired mid-June 2023

Project Description: Egg production in the US is changing from caged to cage-free production. This requires that 72% of laying hens are raised in cage-free housing by 2025. However, there are many different cage-free designs and we don’t know about the performance of hens in these different designs. As more hens are housed in cage-free housing systems, it is important to design systems based on hens’ perceptions and needs, rather than human assumptions. This project aims to understand how hens see the environment so that new cage-free housing can be created that positively impacts hen behavior, productivity and welfare, and food safety. This project will 1) collect information on the laying hens’ eyes, physiology, behavior and welfare in two cage-free housing systems; 2) develop models to estimate how hens see their environment; 3) develop Agent Based Models (ABM) for comparing virtual cage-free housing systems; and 4) build and validate the virtual cage-free system in real life. This approach will facilitate the design of a housing system better suited to the laying hen by reducing unwanted behaviors and improving hen welfare. Egg producers will understand hens’ perceptions and use of the cage-free environment, guiding producers’ decision-making. Additionally, housing manufacturers will have a new approach that could inform the design of future cage-free housing systems.

Position Description/Project Role: The selected post-doctoral scholar will work closely with the entire team (see below) to design, code and implement this ABM under the supervision of Dr. Pat Zollner.

This is a unique opportunity for individuals interested in the interface of individual/agent-based modeling and animal biology. The position provides relevant experience for a career trajectory within a government agency or a research career at a university or non-governmental organizations (NGO). The post-doctoral scholar will be supervised by Dr. Patrick Zollner (Purdue University Department of Forestry and Natural Resources). They will collaborate with: Dr. Darrin Karcher, Dr. Marissa Erasmus, and Dr. Greg Fraley of Purdue’s Department of Animal Sciences as well as Dr. Esteban Fernandez-Juricic from Purdue’s Department of Biology and Dr. Deana Jones US National Poultry Research Center. They will also work closely with representatives from industry throughout model development, testing and implementation. Specific Duties: The post-doctoral scholar will be actively engaged throughout the ABM model development cycle to design, document, implement in code, analyze outputs from a complex agent-based model and prepare/submit manuscripts describing the final products. Successful applicants should expect to do the following:

1) Collaboratively design and develop/code an agent-based model that will integrate inputs from multiple contributors across the project team and stakeholders. Including the ability to plan for this integration, and maintaining iterative versions of model code.

2) Run agent-based modeling software at scale, so that a complex model with thousands of interacting agents can be run hundreds, if not thousands, of times for different analyses working on a computing cluster and/or using cloud-based resources. This skill is required for model testing, calibration, sensitivity analysis, and applied analyses to simulate many stakeholders or researcher-driven alternative management scenarios to assess their relative effectiveness.

3) Use strong code documentation skills (e.g., modeling notebooks, comments in code, etc.) to work with the project team to develop appropriate documentation (ODD, TRACE) of the development and application of this ABM.

4) Use documented scientific writing skills to synthesize this work into manuscripts submitted to journals as final deliverables for this project.

5) Use effective communication skills to interact with stakeholder to ensure their perspectives and concerns are addressed in model development and implementation.

Qualifications: PhD in Computer Programming, Software Engineering, or a related field with an interest in management of cage-free housing systems for egg laying hens. Alternatively, PhD in Biological Sciences or a related discipline with experience in Agent Based Modeling or clearly demonstrated strong quantitative skills.

When preparing materials (statement of interest & response to 5 questions described in how to apply below) applicants should explicitly address their demonstrated organizational skills, interest/background in agent-based modeling, quantitative skills, and their ability to successfully engage with stakeholders. Applicants should be highly motivated with a demonstrated ability to work independently and collaboratively. The post-doctoral scholar that we hire should be able to successfully interact with partners including industry, and government agencies across many levels as well as NGOs. Applicants with experience publishing peer-reviewed journal articles, a strong work ethic, demonstrated technical writing ability, as well as training in quantitative modeling, excellent interpersonal skills, demonstrated skill or skill potential in agent-based modeling will be most competitive. Experience developing individual/agent-based models in NetLogo or equivalent platforms, knowledge related to optimizing solutions to network structure challenges, familiarity with poultry and specifically egg laying industry as well as candidates who bring unique contributions to the diverse perspectives within the Department of Forestry and Natural Resources are all additional elements that will make applicants more competitive.

How to Apply: Interested applicants should compile all of the following materials into a single pdf file; a CV that includes contact information for three professional references, a 1-page statement of interest, and responses to the following 5 questions (each of these responses should be 250 words or less).

1. Describe a situation that demonstrates your work ethic and ability to complete complex tasks in a timely manner.
2. Provide an example of a work/academic situation that typifies how you handle adversity when striving to attain a goal.
3. What motivates you to pursue post-doctoral scholarship, and how will participation in this project prepare you to achieve your career goals?
4. Please describe a specific example from your work/academic experience that demonstrates your curiosity and creativity.
5. What are your strengths and weaknesses with regard to achieving goals individually and in collaboration with others?

That single pdf should be attached to an email that has a subject line of “Application for Post-Doctoral Scholar on Egg Laying Hen ABM”. That email should be sent to Dr. Patrick Zollner ([email protected]) and applicants should understand that their application materials may be reviewed by other project collaborators as part of application evaluation. Application review will begin on June 1 of 2023 and continue until a suitable applicant is hired for the position.

Employment Context: Purdue is a land-grant university of over 40,000 students and ranked the 10th best public university in the U.S. The Department of Forestry and Natural Resources is housed administratively in the College of Agriculture (#7 US ranking) and offers vibrant, nationally ranked graduate programs. Located in West Lafayette, Indiana, Purdue is an easy drive from Indianapolis and Chicago. The West Lafayette-Lafayette area is home to a diverse community of 174,000, with good schools, safe neighborhoods, over 40 parks and extensive trail systems, active Farmers Markets, and year-long community festivals and art events. Purdue University is committed to providing an educational and work environment free of discrimination and harassment and does not condone and will not tolerate discrimination or harassment of any person in the University community.

Contact Persons: Dr. Patrick Zollner Contact Phones: (765) 496-9495 Contact e-mails: [email protected]

Purdue University is an EOE/AA employer. All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply.

An agent-based model to simulate meat consumption behaviour of consumers in Britain (1.0.0)

The current rate of production and consumption of meat poses a problem both to peoples’ health and to the environment. This work aims to develop a simulation of peoples’ meat consumption behaviour in Britain using agent-based modelling. The agents represent individual consumers. The key variables that characterise agents include sex, age, monthly income, perception of the living cost, and concerns about the impact of meat on the environment, health, and animal welfare. A process of peer influence is modelled with respect to the agents’ concerns. Influence spreads across two eating networks (i.e. co-workers and household members) depending on the time of day, day of the week, and agents’ employment status. Data from a representative sample of British consumers is used to empirically ground the model. Different experiments are run simulating interventions of application of social marketing campaigns and a rise in price of meat. The main outcome is the average weekly consumption of meat per consumer. A secondary outcome is the likelihood of eating meat.

Release Notes

work currently under review

Associated Publications

Scalco, A., Macdiarmid, J. I., Craig, T., Whybrow, S. & Horgan, G. W. (2019). An agent-based model to simulate meat consumption behaviour of consumers in Britain. Journal of Artificial Societies and Social Simulation, 22(4), 8 (in press on the 18.10.2019).

Job Opportunity - Netlogo developer

The Department of Defense Management at the Naval Postgraduate School (NPS) seeks applications for a Faculty Associate – Research position to support the Center for Modeling Human Behavior. NPS is a fully accredited graduate school whose students are drawn from the armed forces and civilian agencies of the United States and other countries. CMHB is an interdisciplinary research center integrating advances in psychology, social science, computer modeling, and efficient experimental design to develop and leverage complex human behavior models to address modern defense and security challenges.

Job Description

The primary duties of the position will consist of working collaboratively to maintain and improve complex agent-based simulation models of human behavior in NetLogo. This will include general model improvements of existing models, designing and coding new model components, and research and experimentation with these models. It also includes participation in the development of research proposals, development of new models as new projects arise, improvement of model documentation, and dissemination of research through project reports and peer-reviewed publications. Performance of other typical faculty duties will also be required.

Minimum Qualifications

U.S. Citizenship; Master’s Degree or higher in a relevant degree program; Demonstrated aptitude for scientific research; Demonstrated ability to work with student researchers.

Additional Desired Qualifications

Competence in designing agent-based simulation models; Development experience in NetLogo; Ability to work independently and meet deadlines; Experience working collaboratively on complex modeling projects; Familiarity with general social science concepts; Familiarity with simulation experimental design and data analysis concepts.

This is a non-tenure-track position. The initial appointment will be a part-time position lasting 1 to 3 years with the potential for renewal, and is subject to available funding. The position is eligible for telework. Salary is commensurate with qualifications and experience. This is a federal government position. Benefits and entitlements may be found at https://www.opm.gov.

For more details regarding this opportunity, you can contact: Dr. Susan Aros Department of Defense Management, Naval Postgraduate School Director, Center for Modeling Human Behavior, NPS Lead, The Crowd Dynamics Modeling Group at NPS Lead MORS Human Behavior and Performance Community of Practice [email protected]

Application package

Please send application to DDM Chair Ray Jones at [email protected] including:

Cover letter Curriculum vitae If currently in a PhD program: Letter of recommendation Applications will be accepted beginning immediately and until December 11th, 2022.

NOTE: IF YOU ARE A VETERAN, you are strongly encouraged to identify your Veterans’ Preference on your resume or elsewhere in your application package (type of preference, dates of service, date of VA letter, character of service, etc.)

Additional Veterans’ information: If you are not sure of your preference eligibility, visit the Department of Labor’s website: https://webapps.dol.gov/elaws/vets/vetpref/mservice.htm

For more veterans’ preference information, visit: https://www.fedshirevets.gov/job-seekers/veterans-preference/

The Naval Postgraduate School is an Equal Opportunity/Affirmative Action employer.

Additional information about NPS is available at http://www.nps.edu, and about CMHB is available at https://nps.edu/web/cmhb.

Title: Implementation of a complex agent-based model to address the effects of interacting ecological stressors and alternative management strategies on an endangered species

Institution: Purdue University, Department of Forestry and Natural Resources

Location: Purdue University West Lafayette, IN.

Job Category: Post-Doctoral Scholar or PhD Student

Salary: Commensurate with standards for either a post-doctoral scholar or a PhD student in the Department of Forestry and Natural Resources at Purdue University. The position includes benefits typical for whichever position a candidate is hired for at Purdue University. Duration of Appointment: A post-doctoral scholar will be hired for a minimum of one year and a PhD student for a minimum of three years. The duration of either position is contingent upon completion of ongoing project goals to provide additional funding through 2027.

Start Date: As Soon As Possible for a post-doctoral scholar or January of 2024 for a PhD student.

Project Description: The federally endangered Least Bell’s Vireo (LBVI, Vireo bellii pusillus) nests in narrow riparian areas surrounded by the heavily urbanized matrix of Southern California. Several of the largest remaining patches of LBVI nesting habitat occur on US Department of Defense (DoD) military installations and in US Army Corps of Engineers (USACE) flood control basins. Expenses for ESA compliance related to LBVI are among the highest of all listed bird species, with widespread operational and financial impacts on federal action agencies and military installations. A complex array of threats and stressors interact to threaten LBVI populations, including groundwater extraction, loss of streamflow inputs due to water recycling programs, changing flood and fire regimes, nest parasitism by brown-headed cowbirds (Molothrus ater), and negative impacts to riparian vegetation from invasive non-native plants and insects. One challenge in developing management strategies for recovery is understanding how different stressors may interact, particularly with emerging threats like new invasive species or major changes in disturbance regimes due to climate change. A ~25-minute video describing this project in more detail can be viewed at this link (https://youtu.be/c0DQPcSk-Qg). The goal of this multi-disciplinary, collaborative research project is to develop an individual/agent-based modeling tool that integrates sub-models reflecting different stressors, and synthesizes those sub-models to understand the relative effectiveness of a range of PI- and stakeholder-generated management scenarios.

Position Description/Project Role: The selected person will be supervised within the lab of Dr. Pat Zollner and will work with project Co-PIs (see below) to develop agent-based submodels for Least Bell’s Vireo breeding biology and Brown-headed Cowbird Parasitism. These bird-focused submodels will interact with other process-based (e.g., vegetation succession) and behavior-based (beetle effects on vegetation) submodels, which are being developed by other team members. The aggregation of all sub-models into RESET will allow us to investigate the effects of interacting stressors on vireo habitat and population dynamics in a complex ecological system where applied ecosystem management is common. The applicant will work throughout the entire model development cycle to design, document, and analyze complex agent-based models for vireos and cowbirds using best ABM practices. The project already has a programmer, a current post-doc in Dr. Zollner’s Lab, who is responsible for implementing all agent-based models in code. Therefore, the role of the new post-doctoral scholar or PhD student will be: 1) to focus on designing and documenting structurally realistic bird-focused models 2) interacting with the research team and stakeholders to design and implement simulation experiments and 3) analyzing outputs of simulation experiments to compare potential vireo responses to alternative management scenarios. Finally, the person we hire will prepare journal articles and reports documenting all of the above. Successful applicants will have the following qualifications:

1) Strong skills with scientific writing and preparing reports. As well the ability to read and synthesize extensive data from published papers and technical reports and synthesize important trends from that material.

2) Experience or familiarity with best practices for documenting Agent Based Modeling research (e.g., ODD & TRACE), as well as a commitment to lead in the application of those principles for vireo and cowbird model development.

3) Ability to collaborate with a post-doctoral scholar who is coding this ABM to provide inputs for parameterization, feedback on model design and testing of beta versions of the model.

4) Ability to effectively communicate with external partners and other interested parties to inform designs of scenarios underlying virtual experiments implemented with ABM.

5) Previous experience or interest in learning how to run agent-based modeling software at scale, so that a complex model with thousands of interacting agents can be run hundreds, if not thousands, of times for different analyses working on a computing cluster and/or using cloud-based resources.

This is a unique opportunity for individuals interested in the interface of individual/agent-based modeling, quantitative wildlife conservation, and adaptive management. The position provides relevant experience for a career trajectory within a government agency or a research career at a university or NGO. The post-doctoral scholar will be supervised by Dr. Patrick Zollner (Purdue University Department of Forestry and Natural Resources). New team members will communicate and collaborate regularly with the larger project’s full research team, which includes: Dr. Richard Fischer from the US Army Engineer Research and Development Center; Mr. Casey Lott, Conservation Science and Data Visualization, LLC; Dr. Jeffrey Holland Purdue University Department of Entomology; Ms. Melissa Rohde of Rohde Environmental Consulting LLC; and Dr. Kai-Yin Lin, Purdue University Department of Forestry and Natural Resources.

Specific Duties: The person hired will be responsible for communicating the design, development and application of this ABM. This includes writing and revising ODD model descriptions, contributing to TRACE documentation, and interacting with team members, agency biologists, and the broader scientific community via webinars, conference presentations, and scientific papers. They will play a critical role in engaging with stakeholders to design simulation scenario experiments that integrate sub-models related to different stressors to investigate the implications of management activities. They will collaborate with the research team to prepare and submit manuscripts and reports related describing the results of that research. Responsibility for specific tasks will be assigned on a case-by-case basis but this person will work closely with Dr. Kai-Yin Lin who is coding the model and project Co-PIs on all aspects of this project.

How to Apply: Interested applicants should indicate clearly if they are applying for this position as a PhD student or post-doctoral scholar then they should compile all of the following materials into a single pdf file; a CV that includes contact information for three professional references, a 1-page statement of interest, and responses to the following 7 questions (each of these responses should be 250 words or less). 1. Describe a situation that demonstrates your work ethic and ability to complete complex tasks in a timely manner. 2. Provide an example of a work/academic situation that typifies how you handle adversity when striving to attain a goal. 3. What motivates you to pursue this job, and how will participation in this project help you achieve your career goals? 4. Please describe a specific example from your work/academic experience that demonstrates your curiosity and creativity. 5. What are your strengths and weaknesses with regard to achieving goals individually and in collaboration with others? 6. Why you would be a good fit to fulfill the roles described above for this specific project? 7. What do you find particularly interesting about agent-based modeling in general and this project in particular?

That single pdf should be attached to an email that has a subject line of “Application for Least Bell’s Vireo ABM Project as a postdoctoral scholar” or “Application for Least Bell’s Vireo ABM Project as a PhD student”. That email should be sent to Dr. Patrick Zollner ([email protected]) and applicants should understand that their application materials may be reviewed by other project collaborators as part of application evaluation. Application review will begin as applications are received and continue until a suitable applicant is hired for the position.

Qualifications: Graduate training in wildlife biology, ecological modeling, ornithology, landscape ecology, conservation biology or a related field as well as an interest in Agent Based Modeling and Simulation Modeling to address complex questions in ecological research or applied conservation contexts.

When preparing materials (statement of interest & response to the 7 questions) applicants should explicitly address their scientific writing skills, organizational skills, interest/background in individual/agent-based modeling, quantitative skills, and their ability to work in a team. Applicants should be highly motivated with a documented ability to work independently and collaboratively. The person that we hire should be able to readily interact with partners including government agencies across many levels as well as non-governmental organizations. Applicants with excellent interpersonal skills, experience developing and documenting individual/agent-based models, publishing peer-reviewed journal articles or technical documents, and prior experience with collaborative interdisciplinary projects will be the most competitive. Other skills in quantitative ecology, proficiency in R, familiarity with conservation challenges faced by LBVI, and candidates who bring unique contributions to the diverse perspectives within the Department of Forestry and Natural Resources are all additional elements that will make applicants more competitive.

Purdue is a land-grant university of over 40,000 students and ranked the 10th best public university in the U.S. The Department of Forestry and Natural Resources is housed administratively in the College of Agriculture (#7 US ranking) and offers vibrant, nationally ranked graduate programs in wildlife and ecology. Located in West Lafayette, Indiana, Purdue is an easy drive from Indianapolis and Chicago. The West Lafayette-Lafayette area is home to a diverse community of 174,000, with good schools, safe neighborhoods, over 40 parks and extensive trail systems, active Farmers Markets, and community festivals and art events throughout the year.

Contact Persons: Dr. Patrick Zollner Contact Phones: (765) 496-9495 Contact e-mails: [email protected]

Purdue University is an EOE/AA employer. All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply.

Social Media (1.0.0)

This project attempts to model how social media platforms recommend a user followers based on their interests, and how those individual interests change as a result of the influences from those they follow/are followed by.

We have three types of users on the platform:

Consumers (🔴), who update their interests based on who they’re following. Creators (⬛), who update their interests based on who’s following them. Bots (⚡), who have fixed interests.

All users follow and unfollow another user on the platform every tick. To visually represent each user’s interests, they are assigned a color representing the weighted average of the interests they hold.

Release Notes

Netlogo Version 6.2 is required to run this model.

The sliders on the interface select the initial settings for the model, as well as provide a graphical overview of what interests have taken over the platform. Click SETUP to initialize the users, and GO to begin the simulation. The colors of each user show what interest they believe in most strongly. If a user follows/is followed by another user, it is represented by a directed link to the person being followed.

INITIAL-NUM specifies the number of the users on the platform, while CONSUMER-PROPORTION/CREATOR-PROPORTION/BOT-PROPORTION control the proportions of each type of user.

MIN-SUBS is the minimum amount of links a user can have before they become tired of the platform, and potentially leave, given that SIGN-UP-AND-EXIT is on.

SIGN-UP-AND-EXIT allows new users to sign up every SIGN-UP-RATE ticks, and exit the platform every EXIT-RATE ticks that pass.

Adjusting the sliders on the interface can impact the outcomes of the model in interesting ways, feel free to experiment and see what you find!

Associated Publications

Cellular automata model of social networks (1.0.0)

This project was developed during the Santa Fe course Introduction to Agent-Based Modeling 2022. The origin is a Cellular Automata (CA) model to simulate human interactions that happen in the real world, from Rubens and Oliveira (2009). These authors used a market research with real people in two different times: one at time zero and the second at time zero plus 4 months (longitudinal market research). They developed an agent-based model whose initial condition was inherited from the results of the first market research response values and evolve it to simulate human interactions with Agent-Based Modeling that led to the values of the second market research, without explicitly imposing rules. Then, compared results of the model with the second market research. The model reached 73.80% accuracy. In the same way, this project is an Exploratory ABM project that models individuals in a closed society whose behavior depends upon the result of interaction with two neighbors within a radius of interaction, one on the relative “right” and other one on the relative “left”. According to the states (colors) of neighbors, a given cellular automata rule is applied, according to the value set in Chooser. Five states were used here and are defined as levels of quality perception, where red (states 0 and 1) means unhappy, state 3 is neutral and green (states 3 and 4) means happy. There is also a message passing algorithm in the social network, to analyze the flow and spread of information among nodes. Both the cellular automaton and the message passing algorithms were developed using the Python extension. The model also uses extensions csv and arduino.

Release Notes

There are two types of agents (breeds): clients (person shape) and service providers (star shape). Each one of them carries an internal state from 0 to 4, and also the amount of information, a float starting at 0 (no information at all) and greater than that (amount of information carried). Each agent breed will choose two neighbors within the radius of interaction: an agent with the same breed as itself and an agent of another breed. This set will be used by the cellular automaton algorithm to generate the future state of the agent. Each agent will then move to the XY coordinate between the two neighbors. Note that in the case of lack of two neighbors, the agent can consider its two neighbors as a single other agent. Information starts at level 1.00 for the individual with the biggest degree (connections in the social network), and 0.00 for all the others. It’s possible to note in the plot that the information flows through the network, increasing or decreasing its value over time. Besides the interaction and the formation of social networks and information spread, the system is also subject to levels of temperature of the environment, measured with a sensor attached to Arduino.

Associated Publications

Zimbres, R.A. Modelagem Baseada em Agentes: uma Terceira Maneira de se Fazer Ciência? ANPAD, Presented at Encontro da Associação Nacional de Pós-Graduação e Pesquisa em Administração, Brasil, 2006.

Zimbres, R.A.; Brito, E.P.Z.; Oliveira, P.P.B. Cellular automata based modeling of the formation and evolution of social networks: A case in Dentistry. In: J. Cordeiro and J. Filipe, eds. Proc. of the 10th Int. Conf. on Enterprise Information Systems, INSTICC Press: Setubal-Portugal, Vol. III: Artificial Intelligence and Decision Support Systems, pp. 333–339, 2008.

Zimbres, R.A., Oliveira,P.P.B. Dynamics of Quality Perception in a Social Network: A Cellular Automaton Based Model in Aesthetics Services. Electronic Notes in Theoretical Computer Science, Elsevier, 252 pp 157–180, 2009.

An integrated socio-economic Agent-Based Modeling framework towards assessing farmers’ decision making under water scarcity and varying utility function (6.1.1)

A spatio-temporal Agent Based Modeling (ABM) framework is developed to probabilistically predict farmers’ decisions in the context of climate-induced water scarcity under varying utility optimization functions. The proposed framework forecasts farmers’ behavior assuming varying utility functions. The framework allows decision makers to forecast the behavior of farmers through a user-friendly platform with clear output visualization. The functionality of the proposed ABM is illustrated in an agriculturally dominated plain along the Eastern Mediterranean coastline.

Study area GIS data available upon request to [email protected]

Release Notes

The model aims at predicting the decision of farmer under the context of water scarcity and future land use changes. The model runs on an annual basis.

Associated Publications

FeedUS - A global food trade model (1.1.0)

The purpose of the model is to study the impact of global food trade on food and nutrition security in countries around the world. It will incorporate three main aspects of trade between countries, including a country’s wealth, geographic location, and its trade relationships with other countries (past and ongoing), and can be used to study food and nutrition security across countries in various scenarios, such as climate change, sustainable intensification, waste reduction and dietary change.

Release Notes

FEEDUS Model version 20181112 with updated data files

Associated Publications

BEEHAVE Extension: Varroa mite control within Good Beekeeping Practice in Germany (1.1.0)

The western honey bee Apis mellifera is the most important pollinator in the world. The biggest threat to managed honey bees is the ectoparasitic mite Varroa destructor and the viruses DWV (Deformed Wing Virus) and APV (Acute Paralysis Virus) it transmits. Untreated honey bee colonies are expected to die within one to three years. This led to the development of strategies for beekeepers to control the Varroa mite in honey bee colonies and ensure the health and survival of their bee colonies, so called Good Beekeeping Practice. The aim of the extension of BEEHAVE was to represent the Good Beekeeping Practice of Varroa control in Germany. The relevant measures within the Varroa control strategies are drone brood removal as a Varroa trap and the treatment of bee colonies with organic acaricides (formic and oxalic acid) to kill the mites. This extension improves BEEHAVE and builds a bridge between beekeepers in practice and in the modelling world. It vastly contributes to the future use of BEEHAVE in beekeeping education in Germany.

Release Notes

Addition to the existing BEEHAVE model BEEHAVE_BeeMapp2016 (download under https://www.beehave-model.net). The newly implemented module allows the user to execute varroa mite control strategies, according to the Good Beekeeping Practice, as done in Germany in BEEHAVE.

Associated Publications

MeReDiem : Fallow Land Simulations to examine the conditions of sustainable village livelihood (1.0.1)

The MeReDiem model aims to simulate the effect of socio-agricultural practices of farmers and pastors on the food sustainability and soil fertility of a serrer village, in Senegal. The model is a central part of a companion modeling and exploration approach, described in a paper, currently under review)

The village population is composed of families (kitchens). Kitchens cultivate their land parcels to feed their members, aiming for food security at the family level. On a global level , the village tries to preserve the community fallow land as long as possible.

Kitchens sizes vary depending on the kitchens food production, births and migration when food is insufficient. Solidarity practices in form of parcels loans and food donations are triggered whenever a kitchen is in deficit and another can provide help. Agricultural practices consist in cattle manure usage , faidherbia trees preservation, crop rotation cycle choice and the propension to use fallow land. Basic soil fertility process allow to incorporate the effects of farmers practices on crops yields alongside rainfall.

Agricultural and social mechanisms have been designed according to the village actors sayings. A couple of variations of these mechanisms are provided to represent the observed diversity of practices and in order to test alternative scenarios. The alternative scenarios are used to stimulate discussion with actors , as the primary purpose pursued by the model is social learning.

Release Notes

Update of the previous release (1.0.0) with the correct code directory organization

Associated Publications

this version of the model is associated to a paper currently under review

Design principles for a redistributive collective action institution in times of crisis (1.0.0)

What policy measures are effective in redistributing essential resources during crisis situations such as climate change impacts? We model a collective action institution with different rules for designing and organizing it, and make our analysis specific to various societal contexts.

Our model captures a generic societal context of unequal vulnerability and climate change impact in a stylized form. We represent a community of people who harvest and consume an essential resource to maintain their well-being. However, their ability to harvest the resource is not equal; people are characterized by a ‘resource access’ attribute whose values are uniformly distributed from 0 to 1 in the population. A person’s resource access value determines the amount of resource units they are able to harvest, and therefore the welfare levels they are able to attain. People travel to the centralized resource region and derive well-being or welfare, represented as an energy gain, by harvesting and consuming resource units.

The community is subject to a climate change impact event that occurs with a certain periodicity and over a certain duration. The capacity of resource units to regenerate diminishes during the impact events. Unequal capacities to access the essential resource results in unequal vulnerability among people with regards to their ability to maintain a sufficient welfare level, especially during impact events.

To help people maintain their welfare above the sufficiency threshold, the community can set up and operate a ‘resource bank’, which represents a collective action institution that facilitates the redistribution of essential resources in communities. The key characteristics of this institution that we stylize are the cost of setting it up and operating it, its operational lifetime, and the aggregation technology it functions as. In addition, we also seek to represent policy instruments relevant to the institution, viz. different tax policies to fund the collective action institution, and the urgency of this adaptive action, i.e. the level of societal impact needed to motivate it.

In particular, we are interested in evaluating the effects of the following conditions and policies (or rules): 1. The social and political barriers to equitable participation (or inclusion) in decision-making (re. operating the collective action institution); 2. The urgency of the decision-making process, i.e. the level of societal impact or damage needed to motivate it; the impact of the tax policy that funds the collective action institution, as well as the nature of the institution in terms of how it can translate individual contributions to public benefits; and 3. The operational lifetime of the collective action institution, which determines its overall cost, the time period for which it is accessible to those in need, and the frequency with which the decision to set up the institution is made.

Release Notes

Version 1.0.0 is the first release of this model.

Associated Publications

Myside Bias and Group Discussion (1.0.0)

The my-side bias is a well-documented cognitive bias in the evaluation of arguments, in which reasoners in a discussion tend to overvalue arguments that confirm their prior beliefs, while undervaluing arguments that attack their prior beliefs. This agent-based model in Netlogo simulates a group discussion among myside-biased agents, within a Bayesian setting. This model is designed to investigate the effects of the myside bias on the ability of groups to reach a consensus or collectively track the correct answer to a given binary issue.

Release Notes

The model simulates a group discussions over a binary issue between myside biased agents, i.e. agents that undervalue arguments that attack their prior belief, and overvalue arguments that confirm their prior belief. The objective of our model is to assess the extent to which the myside bias, i.e. the tendency to overvalue/undervalue arguments depending on their fit with one’s own prior belief, affect the ability of the group to find the correct answer to the binary issue under discussion. In particular, the model is built to answer the question: does the myside bias help or hinder the ability of groups to find the correct answer to a binary issue?

Associated Publications

The Wisdom of the Small Crowd: Myside Bias and Group Discussion, with Zoé Christoff, Stephan Hartmann and Rineke Verbrugge, Journal of Artificial Societies and Social Simulations (forthcoming)

Systems Special Issue: Integrating System Dynamics with AI and Other Analytical Methods: Advancements and Applications for Decision Making with/within Complex Systems

MABS 2022 – The 23rd Multi-Agent-Based Simulation Workshop hosted at AAMAS 2022 (Auckland, New Zealand) May 9-10, 2022

Website: https://mabsworkshop.github.io/

==Call for Papers== MABS 2022 is part of the AAMAS 2022 conference taking place in Auckland, New Zealand on May 9-13, 2022.

We welcome your paper submissions from all areas of multi-agent-based simulation and particularly also of work in early stages, which can benefit from active discussions.

==Relevant Topics== The range of technical issues that MABS has dealt with, and continues to deal with, is quite diverse and extensive. Topics relevant to this workshop include, but are not limited to, the following: • Simulation methodologies (Standards for MABS, Methodologies and simulation languages for MABS, Simulation platforms and tools for MABS, Visualization and analytic tools, Approaches for large-scale simulations, Scalability and robustness in MABS, Future challenges in MABS) • Simulation of Social and Intelligent behavior (Formal and agent models of social behavior, Cognitive modelling and simulation, Game theory and simulation, Social structure, social networks and simulating organizations, Simulating social complexity) • Applications and Empirical Work (MABS in environmental organizations, MABS and cloud computing, Agent-based experimental economics, Participative-based simulation, MABS and games, MABS in governance and policymaking) • Simulation Analytics (Application of data analytics and machine learning methods to the analysis of large-scale simulations)

The ongoing COVID-19 pandemic has brought about renewed interest in modelling of disease (and measures to control it) in societies. We intend for 2022 to include a special session on simulations related to the crisis, e.g., Modelling of transmission processes, societies, or effects of interventions. We especially encourage the submission of novel and original approaches that are not fully developed and can benefit from discussions.

==Target Audience== The workshop will provide a forum for social scientists, MAS and AI researchers and developers, as well as simulation researchers, to assess the current state of the art in the modelling and simulation of social systems and MAS, to identify where existing approaches can be successfully applied, to learn about new approaches and explore future research challenges, and to exchange ideas and knowledge in an inter-disciplinary environment. The workshop will be of interest to researchers engaged in modelling and analysis of multi-agent systems, and those interested in applying agent-based simulation techniques to real-world problems. In addition, it will attract researchers committed to cross-cutting research that is complementary to more orthodox modelling approaches.

MABS intends to be a place where researchers can exchange ideas about their work and we are looking forward to the community meeting once again in person. At the same time, we are also planning for the possibility that the global public health situation might require us to run the workshop as a partly or fully virtual event. In such a context, we will adapt the program and provide the tools so that researchers from all around the world can participate to the event. Even in an online workshop, we will endeavor to create the space for informal exchange of ideas and to get to know each other, for example in panel discussions or digital break-out rooms on topics identified during the workshop by the participants.

==Submission of Papers (Deadline: Feb 6, 2022)== Submissions are limited to 12 pages formatted according to Springer LNCS style and must be electronically submitted before the submission deadline through the workshop conference system, which is available at: https://easychair.org/conferences/?conf=mabs2022. All contributions will be peer-reviewed by two or three independent PC members. The evaluation criteria of contributions will be based on originality, quality, clarity, and its relevance to the workshop. All accepted papers will be printed in the AAMAS workshop proceedings. In addition, following the tradition of the previous MABS workshops, we intend to publish the accepted papers, after a further reviewing process, in the Springer Multi-Agent-Based Simulation book series, LNAI.

==Important Dates== Submission deadline: extended to: Feb 6, 2022 Notification of acceptance or rejection: Feb 27, 2022 Camera ready versions: Mar 6, 2022 MABS 2022 will take place: May 9-10, 2022

Submissions (EasyChair): https://easychair.org/conferences/?conf=mabs2022 CFP: https://easychair.org/cfp/MABS2022

For further questions related to the workshop, please email mabs2022(at)easychair(dot)org or visit https://mabsworkshop.github.io/.

==Program Chairs== Emma Norling and Fabian Lorig on behalf of the MABS Steering Committee

Computational Social Scientist, 4-month+ Contract with sistemaFutura

Title: Modeling Interacting Stressors & Management Strategies on Least Bell’s Vireo Populations

Institution: Purdue University, Department of Forestry and Natural Resources

Location: West Lafayette, IN

Job Category: Post-Doctoral Scholar

Salary: Commensurate with selected candidates experience and standards for Post-doctoral scholars in the Department of Forestry and Natural Resources at Purdue University.

Duration of Appointment: Applicant will be hired for a minimum of one year. Funding is available to support a post-doctoral scholar for the four-year duration of this project pending approval of additional funds after the completion of the first two project years.

Pertinent Websites: https://www.purdue.edu/fnr/sites/zollner/

Start Date: August 15 2022. Funding may be available for the selected candidate to start earlier in the summer of 2022 if they prefer.

Description: The federally endangered Least Bell’s Vireo (LBVI, Vireo bellii pusillus) nests in narrow riparian areas surrounded by the heavily urbanized matrix of Southern California. Several of the largest remaining patches of LBVI nesting habitat occur on US Department of Defense (DoD) military training areas and in US Army Corps of Engineers (USACE) flood control basins. Expenses for ESA compliance related to LBVI are among the highest of all listed bird species, with widespread operational and financial impacts on federal action agencies and military installations. A complex array of threats and stressors interact to threaten LBVI populations, including groundwater extraction, loss of streamflow inputs due to water recycling programs, changing flood and fire regimes, nest parasitism by brown-headed cowbirds (Molothrus ater), and negative impacts to riparian vegetation from invasive non-native plants and insects. One challenge in developing management strategies for recovery is understanding how different stressors may interact, particularly with emerging threats like new invasive species or major changes in disturbance regimes due to climate change. A ~25-minute video describing this project in more detail can be viewed at this link (https://youtu.be/c0DQPcSk-Qg). The goal of this research project is to develop an individual/agent-based modeling tool that integrates sub-models reflecting different stressors, and synthesizes those sub-models to understand the relative effectiveness of a range of PI- and stakeholder-generated management scenarios. The selected post-doctoral scholar will work closely with PhD students in the labs of Dr. Pat Zollner and Dr. Jeff Holland as well as with all project Co-PIs (see below) and end users to fill these knowledge gaps by addressing 3 objectives:

1) designing, developing, and implementing an agent-based model that integrates sub-models (developed by collaborators) associated with multiple stressors to assess their interactive influence upon LBVI populations;

2) collaborating with relevant agency and NGO partners to design a spectrum of realistic management scenarios across the LBVI range and use the agent based model to simulate these scenarios and assess their relative effectiveness; and

3) publishing manuscripts describing the research underlying the first two objectives and delivering the agent based model and documentation to end users.

This is a unique opportunity for individuals interested in the interface of individual/agent-based modeling, quantitative ecology, wildlife biology, conservation biology and ornithology. The position provides applied experience for a career trajectory in local, state, or federal agencies or a research career focused on the fields of quantitative ecology or conservation biology. The post-doctoral scholar will be advised by Dr. Patrick Zollner (Purdue University Department of Forestry and Natural Resources). The student’s research will be a collaboration with; Dr. Richard Fischer from the US Army Engineer Research and Development Center, Mr. Casey Lott Conservation Science and Data Visualization, LLC, Dr. Jeffrey Holland Purdue University Department of Entomology, and Ms. Melissa Rohde of CA TNC.

Specific Duties: The post-doctoral scholar will serve as the hub coordinating the design and code compatibility of sub-models from all project collaborators. They will play a critical role in designing and coding the overarching model that integrates sub-models related to different stressors as well simulation experiments that investigate the interactive effects of those stressors and their implications for management activities. Responsibility for specific tasks will remain TBD until the entire team is assembled and the relative strengths and interests of all participants have been assessed.

How to Apply: Interested applicants should compile all of the following materials into a single pdf file; a CV that includes contact information for three professional references, a 1-page statement of interest, and responses to the following 5 questions (each of these responses should be 250 words or less).

1. Describe a situation that demonstrates your work ethic and ability to complete complex tasks in a timely manner.
2. Provide an example of a work/academic situation that typifies how you handle adversity when striving to attain a goal.
3. What motivates you to pursue post-doctoral scholarship, and how will participation in this project prepare you to achieve your career goals?
4. Please describe a specific example from your work/academic experience that demonstrates your curiosity and creativity.
5. What are your strengths and weaknesses with regard to achieving goals individually and in collaboration with others?

That single pdf should be attached to an email that has a subject line of “Application for Post-Doctoral Scholar on Least Bell’s Vireo ABM”. That email should be sent to Dr. Patrick Zollner ([email protected]) and applicants should understand that their application materials may be reviewed by other project collaborators as part of application evaluation. Application review will begin 8:00 AM on June 6 2022.

Qualifications: PhD in Ecological Modelling, Wildlife Biology or a related discipline.

When preparing materials (statement of interest & response to 5 questions) applicants should explicitly address their demonstrated organizational skills, interest/background in individual/agent-based modeling, quantitative skills, and their ability to mentor others. Applicants should be highly motivated with a demonstrated ability to work independently and collaboratively. The post-doctoral scholar that we hire should be able to readily interact with partners including government agencies across many levels as well as non-governmental organizations. Applicants with experience publishing peer-reviewed journal articles, a strong work ethic, demonstrated technical writing ability, training in ecological modeling, excellent interpersonal skills, demonstrated skill or skill potential in quantitative ecology and proficiency in R will be most competitive. Experience developing individual/agent-based models in NetLogo or equivalent platforms, knowledge related to optimizing solutions to network structure challenges, familiarity with conservation challenges faced by LBVI, as well as candidates who bring unique contributions to the diverse perspectives within the Department of Forestry and Natural Resources are all additional elements that will make applicants more competitive.

Purdue is a land-grant university of over 40,000 students and ranked the 10th best public university in the U.S. The Department of Forestry and Natural Resources is housed administratively in the College of Agriculture (#7 US ranking) and offers vibrant, nationally ranked graduate programs in wildlife and ecology. Located in West Lafayette, Indiana, Purdue is an easy drive from Indianapolis and Chicago. The West Lafayette-Lafayette area is home to a diverse community of 174,000, with good schools, safe neighborhoods, over 40 parks and extensive trail systems, active Farmers Markets, and year-long community festivals and art events.

Contact Persons: Dr. Patrick Zollner Contact Phones: (765) 430-7858 Contact e-mails: [email protected]

Agent-based model of team decision-making in hidden profile situations (1.0.0)

The model presented here is extensively described in the paper ‘Talk less to strangers: How homophily can improve collective decision-making in diverse teams’ (forthcoming at JASSS). A full replication package reproducing all results presented in the paper is accessible at https://osf.io/76hfm/.

Narrative documentation includes a detailed description of the model, including a schematic figure and an extensive representation of the model in pseudocode.

The model develops a formal representation of a diverse work team facing a decision problem as implemented in the experimental setup of the hidden-profile paradigm. We implement a setup where a group seeks to identify the best out of a set of possible decision options. Individuals are equipped with different pieces of information that need to be combined to identify the best option. To this end, we assume a team of N agents. Each agent belongs to one of M groups where each group consists of agents who share a common identity. The virtual teams in our model face a decision problem, in that the best option out of a set of J discrete options needs to be identified. Every team member forms her own belief about which decision option is best but is open to influence by other team members. Influence is implemented as a sequence of communication events. Agents choose an interaction partner according to homophily h and take turns in sharing an argument with an interaction partner. Every time an argument is emitted, the recipient updates her beliefs and tells her team what option she currently believes to be best. This influence process continues until all agents prefer the same option. This option is the team’s decision.

Release Notes

first release

Associated Publications

forthcoming

4. Programmer and visualization specialist

A Computational Simulation for Task Allocation Influencing Performance in the Team System (1.0.0)

This model system aims to simulate the whole process of task allocation, task execution and evaluation in the team system through a feasible method. On the basis of Complex Adaptive Systems (CAS) theory and Agent-based Modelling (ABM) technologies and tools, this simulation system attempts to abstract real-world teams into MAS models. The author designs various task allocation strategies according to different perspectives, and the interaction among members is concerned during the task-performing process. Additionally, knowledge can be acquired by such an interaction process if members encounter tasks they cannot handle directly. An artificial computational team is constructed through ABM in this simulation system, to replace real teams and carry out computational experiments. In all, this model system has great potential for studying team dynamics, and model explorers are encouraged to expand on this to develop richer models for research.

Release Notes

This simulation system is based on a preliminary model to explore the relationship between individual components and group level of performance. This system aims to focus on the impact of interaction among members on group performance under different task allocation strategies, and mainly paying attention to the influence of a single allocation outcome on interpersonal interactions and group performance.

Associated Publications

(1) Wang, S., Dang, Y. & Wu, J. How Task Allocation Strategy Affects Team Performance: A Computational Experiment. J. Syst. Sci. Syst. Eng. 27, 656–676 (2018). https://doi.org/10.1007/s11518-018-5387-3 (2) Wang, S., Dang, Y., Wu, J. (2017). The Effect of Task Allocation Strategy on Knowledge Intensive Team Performance Based on Computational Experiment. In: Chen, J., Theeramunkong, T., Supnithi, T., Tang, X. (eds) Knowledge and Systems Sciences. KSS 2017. Communications in Computer and Information Science, vol 780. Springer, Singapore. https://doi.org/10.1007/978-981-10-6989-5_19

Dear Colleagues,

In recent years, our society has been challenged by numerous societal threats that have emerged from different sources. Many events have threatened democratic values, such as online election manipulation, radicalization, the “normalization” of extreme behavior, and the re-emergence of racist phenomena across all the spectra of social life. Additionally, other events have brought political instability, conflicts, and terrorist activities, while others are still posing significant challenges for dealing with climate change, appropriately responding to global epidemics, and sustainably managing natural resources. For example, the recent events in Afghanistan illustrate how fringe, extremist groups can still rise to prominence with blind attacks (Kabul airport), while at the same time, the world is still trying to understand how the Taliban will govern and what the consequences in the area, in terms of both the power dynamics (the power balance in the Middle East) and the exploitation and management of natural resources (oil and gas lines, rare minerals, etc.), will be.

Thus, it has become critical to design policies that mitigate these threats without producing unintended consequences for our society or planet, or infringing on fundamental human rights, which the United Nations proclaimed in 1948 in a document entitled the “Universal Declaration of Human Rights” (https://www.un.org/en/about-us/universal-declaration-of-human-rights) (UDHR).

We believe that addressing and better understanding these issues could benefit from the application of systemic and quantitative methods (e.g., analytical methods, different simulation paradigms, optimization techniques, probabilistic approaches, etc.), regardless of whether such challenges are not easily quantified, are dynamic and history-dependent, are composed of many tightly coupled interdependent factors, and contain many nonlinear relationships and delays. Addressing these issues is challenging because they are often counterintuitive, as cause and effect are distant in time and space, resistant to intervention policies, and commonly characterized by trade-offs between short- and long-term impacts and goals.

Examples of such approaches are neither new nor isolated. For example, Sandberg (2000) used system dynamics to investigate the routes of democracy’s global diffusion from 1800 until 2000. Stave (2002) used simulation to illustrate how public participation in environmental decisions can be improved, while Hirsch et al. (2007) modeled how educational reform can impact society. Só et al. (2017) used a system dynamics model to investigate the vicious cycle of low human development observed in Guinea-Bissau, in which the authors found political instability and several coups among its root causes. Finally, Armenia et al. (2020) used systemic thinking and system dynamics to illustrate how racism permeates football and how it can be dealt with.

The methodology is not limited to such general societal issues; specific problems are also addressed. Armenia and Sellito (2014) asserted that quantitative methods can be used to detect acts of opinion manipulation in online forums, Armenia and Tsaples (2017) used epidemiological models to analyze how individual behavior could help or hinder the diffusion of cyberthreats, and finally, Pruyt et al. (2015) used system dynamics to help policymakers to design and test the effectiveness of policies enacted to mitigate the consequences of foreign fighters.

However, such issues are not addressed only through simulation and system dynamics. Armenia and Sellitto (2014) outlined a framework that combines simulation, network analysis, and control theory with the purpose of supporting regional impact analysis. Finally, other methodologies such as game theory have a long tradition in dealing with issues, from voting (Brams, 2008); (Kling, Kunegis, Hartmann, Strohmaier, & Staab, 2015) to designing strategies for searching communities in networks (Narayanam & Narahari, 2012).

Our society is facing severe environmental challenges that threaten our survival and endanger the future of our planet. One iconic study was published by Meadows et al. (1972), where the authors, using a computer simulation model, concluded that, without drastic changes to resource consumption patterns and due to the uncontrolled population and economic growth, the Earth would be doomed to ecological overshoot and pending disaster. Since then, several studies have explored many aspects of these environmental challenges, such as global warming, severe climate changes, water supply crises due to climate-change effects, energy transition (i.e., aiming at renewable and sustainable sources), etc.

The Special Issue is focused on applying such methods to subjects that somehow impose threats to our society, our planet, and proclaimed fundamental human rights, which can manifest in several domains. Studies that use these methods in the following areas (for example, but not limited to these) are sought:

• Bullying;
• The management of renewable and nonrenewable natural resources;
• Global warming and climate change;
• Energy transition and decarbonization;
• Epidemics and health policies;
• Online meddling in elections;
• Political instability and conflicts;
• Racism in society and racism in sports;
• Radicalization and measures to prevent it;
• Terrorist organizations and activities;
• Waste management.

The methods could include but are not limited to the following:

• Agent-based modeling;
• Discrete events;
• Optimization;
• Multi-criteria decision aids;
• Game theory;
• Graph theory;
• Probabilistic methods;
• Network analysis;
• System dynamics;
• Hybrid approaches and combinations of all the above.

Dr. Stefano Armenia Dr. George Tsaples Dr. Eduardo Ferreira Franco Guest Editors

Agent-Based Model of Transhumant Decision-Making Processes in Senegal (1.0.0)

Sahelian transhumance is a type of socio-economic and environmental pastoral mobility. It involves the movement of herds from their terroir of origin (i.e., their original pastures) to one or more host terroirs, followed by a return to the terroir of origin.  According to certain pastoralists, the mobility of herds is planned to prevent environmental degradation, given the continuous dependence of these herds on their environment. However, these herds emit Greenhouse Gases (GHGs) in the spaces they traverse. Given that GHGs contribute to global warming, our long-term objective is to quantify the GHGs emitted by Sahelian herds. The determination of these herds’ GHG emissions requires: (1) the artificial replication of the transhumance, and (2) precise knowledge of the space used during their transhumance. This article presents the design of an artificial replication of the transhumance through an agent-based model named MSTRANS. MSTRANS determines the space used by transhumant herds, based on the decision-making process of Sahelian transhumants. MSTRANS integrates a constrained multi-objective optimization problem and algorithms into an agent-based model. The constrained multi-objective optimization problem encapsulates the rationality and adaptability of pastoral strategies. Interactions between a transhumant and its socio-economic network are modeled using algorithms, diffusion processes, and within the multi-objective optimization problem. The dynamics of pastoral resources are formalized at various spatio-temporal scales using equations that are integrated into the algorithms. The results of MSTRANS are validated using GPS data collected from transhumant herds in Senegal. MSTRANS results highlight the relevance of integrated models and constrained multi-objective optimization for modeling and monitoring the movements of transhumant herds in the Sahel. Now specialists in calculating greenhouse gas emissions have a reproducible and reusable tool for determining the space occupied by transhumant herds in a Sahelian country. In addition, decision-makers, pastoralists, veterinarians and traders have a reproducible and reusable tool to help them make environmental and socio-economic decisions.

Release Notes

None

Associated Publications

https://doi.org/10.18564/jasss.5445

A Computational Simulation for Task Allocation Influencing Performance in the Team System (1.1.0)

This model system aims to simulate the whole process of task allocation, task execution and evaluation in the team system through a feasible method. On the basis of Complex Adaptive Systems (CAS) theory and Agent-based Modelling (ABM) technologies and tools, this simulation system attempts to abstract real-world teams into MAS models. The author designs various task allocation strategies according to different perspectives, and the interaction among members is concerned during the task-performing process. Additionally, knowledge can be acquired by such an interaction process if members encounter tasks they cannot handle directly. An artificial computational team is constructed through ABM in this simulation system, to replace real teams and carry out computational experiments. In all, this model system has great potential for studying team dynamics, and model explorers are encouraged to expand on this to develop richer models for research.

Release Notes

This simulation system is based on a preliminary model to explore the relationship between individual components and group level of performance. This system aims to focus on the impact of interaction among members on group performance under different task allocation strategies, and mainly pay attention to the influence of a single allocation outcome on interpersonal interactions and group performance.

Associated Publications

(1) Wang, S., Dang, Y. & Wu, J. How Task Allocation Strategy Affects Team Performance: A Computational Experiment. J. Syst. Sci. Syst. Eng. 27, 656–676 (2018). https://doi.org/10.1007/s11518-018-5387-3 (2) Wang, S., Dang, Y., Wu, J. (2017). The Effect of Task Allocation Strategy on Knowledge Intensive Team Performance Based on Computational Experiment. In: Chen, J., Theeramunkong, T., Supnithi, T., Tang, X. (eds) Knowledge and Systems Sciences. KSS 2017. Communications in Computer and Information Science, vol 780. Springer, Singapore. https://doi.org/10.1007/978-981-10-6989-5_19

Models associated with paper entitled "Polarization in Social Media: A Virtual Worlds-Based Approach" (1.0.0)

This model contains MATLAB code describing the virtual worlds framework used in the paper entitled “Polarization in Social Media: A Virtual Worlds-Based Approach.” The parent directory contains driver code for replicating results from the paper. Additionally, the source code is structured by three directories:

• Data Structures: Contains classes and objects used in the code, such as the virtualWorlds.m
• Metrics: Contains code which computes metrics, such as congruentLinks.m
• Visualization: Contains code for generating pictures and plots, such as drawSystemState.m

Please see the README file within the source code for more information.

Release Notes

Initial release

Associated Publications

Source code for the paper “Polarization in Social Media: A Virtual Worlds-Based Approach” in Journal of Artificial Societies and Social Simulation 26 (3) 11. The URL link is the following: https://www.jasss.org/26/3/11.html