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Multi-AI consensus MCP server that queries multiple AI models (OpenAI, Claude, Gemini, custom APIs) in parallel and synthesizes responses to reduce bias and improve accuracy. A Python implementation of the wisdom-of-crowds approach for AI decision making.
The repository contains data and scripts for the study "From Prediction Markets to Interpretable Collective Intelligence" by Alexey V. Osipov and Nikolay N. Osipov (arXiv:2204.13424 [cs.GT]).
This shall be a guide for beginners, intermediates as well as professionals to adapt best practices and to enhance code quality. Feel free to contribute. Let's get 02/02/2020 best practices into the ice!
I am working on publishing a paper on approximating solutions to the Vehicle Routing Problem using Wisdom of Artificial Crowds with Genetic Algorithms. This is a continuation of work started in Professor Roman Yampolskiy's Artificial Intelligence class.
This project evaluates whether the wisdom of the crowd improves wage prediction accuracy. Multiple regression models—Linear, Ridge, KNN, Decision Tree, and SVR—are compared against a tuned VotingRegressor ensemble to determine if the ensemble outperforms individual models.