Decentralized Multi-Agent Reinforcement Learning for General (incl Continuous) State and Action Spaces
[below needs updating] The repository includes the following:
-
multi_agent_learning.py
: module implementing the multi-agent Q-learning algorithm. -
br_graph_analysis.py
: module for learning and analyzing the best-reply graph of a game problem. -
team_learning.py
: module implementing decentralized team-learning algorithm. -
sim_utils.py
: module containing some basic utility functions for running simulations. -
look at the
notebooks
folder for examples using these modules (the notebooks are varied in content; at the moment this is just a dump of various experiments that are part of the research project).