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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.
Prisoner's Dilemma algorithms developed using Python and Jupyter Notebook based programming languages for social decision-making research in socially anxious populations.
This project is a computer simulation of a multi-agent extended prisoner’s dilemma using manipulation. The aim is to investigate if the outcome for all agents is better with or without the possibility of manipulation.