A research tool for the Iterated Prisoner's Dilemma
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Updated
Jul 12, 2024 - Python
A research tool for the Iterated Prisoner's Dilemma
Trains machine learning strategies for the IPD with evolutionary and particle swarm algorithms, including neural networks and finite state machines
Code for our PLOS ONE paper: "Predicting Human Decision Making in Psychological Tasks with Recurrent Neural Networks"
This is a model plugin for Evoplex. It implements the spatial prisoner's dilemma game proposed by Nowak, M. A., & May, R. M. (1992). Evolutionary games and spatial chaos. Nature, 359(6398), 826.
Computational analysis and data visualization tool for the Prisoner's Dilemma.
A tool to analyze strategies for the Iterated Prisoner's Dilemma
Code and materials for the paper S. Phelps and Y. I. Russell, Investigating Emergent Goal-Like Behaviour in Large Language Models Using Experimental Economics, working paper, arXiv:2305.07970, May 2023
Simulation of agents competing for resources with different strategies
Prisoner's Dilemma algorithms developed using Python and Jupyter Notebook based programming languages for social decision-making research in socially anxious populations.
The prisoner's dilemma in python
A practical look at the Axelrod tournament.
A prisoner's dilemma agent based model simulation for investigating effects of differing strategies on emergent behaviours and spatial patterns with configurable environments.
A minimalist multi-agent implementation of the social dilemma problem with governance kernels
Behavioral economic games with interface to showcase at events
This program simulates and quantifies outcomes of parameterized prisoner’s dilemma simulation in various MAS networks. This is the third lab in the series of 3 lab projects designed to introduce Multi-Agent Systems (MAS) as a base for Machine Learning.
Agent-based model of multi-level group selection
Multi-agent system for modeling trust in market exchanges.
Based on Veritasium's video on Primoner's Dilemma
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