Reinforcement learning approach to the prisoner's dilemma, based on Q learning
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Updated
Dec 1, 2017 - Python
Reinforcement learning approach to the prisoner's dilemma, based on Q learning
A prisoner's dilemma agent based model simulation for investigating effects of differing strategies on emergent behaviours and spatial patterns with configurable environments.
Recreation of the prisoner's dilemma model from Axelrod's "Evolution of Cooperation" in Python
Simulator for the classical prisoner dilemma game.
Implements several strategies and the overall tournament functions
An implementation of iterative prisoner dilemma with reinforcement learning via q_table (NOT DQN) in Python with around 30 strategies
Prisoner's-Dilemma-Tournament-Mode
Iterative Prisoner Dilemma - Tournament of 20+ classic strategies and an ML player built with DQN
The prisoner's dilemma in python
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