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14 public repositories
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This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled by ''Shapley Q-value: A Local Reward Approach to Solve Global Reward Games''.
Updated
Feb 26, 2020
Python
Implementation of Multi-Agent Reinforcement Learning algorithm(s). Currently includes: MADDPG
Updated
Jul 9, 2019
Python
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray (RLLib) is used for training.
Updated
Jul 22, 2020
Jupyter Notebook
Implementation of Deep Reinforcement Learning from Self-Play in Imperfect-Information Games (Heinrich and Silver, 2016)
Updated
Nov 30, 2018
Python
A simple example of how to implement vector based DDPG for MARL tasks using PyTorch and a ML-Agents environment.
Updated
Dec 23, 2018
Python
Multi-agent reinforcement learning framework
Updated
Aug 13, 2020
Python
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
Emergence of complex strategies through multiagent competition
Updated
Jul 13, 2020
Python
Team-based Multi-agent Reinforcement Learning
Updated
Feb 7, 2019
Jupyter Notebook
This is one component of Cross-functional Team-based Multi-agent (CTMA) framework.
Updated
Apr 19, 2019
Jupyter Notebook
Pytorch implementation of MADDPG algorithm
Updated
Feb 12, 2020
Python
My attempt to implement a water down version of PBT (Population based training) for MARL (Multi-agent reinforcement learning).
Updated
Aug 4, 2020
Jupyter Notebook
Updated
Jan 9, 2019
Jupyter Notebook
Multi-Agent reinforcement learning, goal is to train an agent to solve the Physical Deception problem.
Updated
May 26, 2020
Python
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