Skip to content

franklinnwren/Flowcomm

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 

Repository files navigation

Flowcomm

Code for "Learning Correlated Communication Topology in Multi-Agent Reinforcement Learning" experiment in multiagent particle world for the amended cooperative navigation task "simple_spread_local" and "simple_spread_hetero".

We use MAAC (Iqbal, et al) as our base algorithm and integrate our graph modele to the original algorithm.

To run the code, first install the MPE in the particle_env folder, type shell command "pip install -e .".

Then, in the base directory, type "python main.py simple_spread_local maac", the default number of agents is 4. For the hetero task, the default number of agents is 8.

About

Code for "Learning Correlated Communication Topology in Multi-Agent Reinforcement Learning" experiments.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages