# MAPPO

**Repository Path**: yuanzicode/MAPPO

## Basic Information

- **Project Name**: MAPPO
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-04-27
- **Last Updated**: 2025-04-27

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# MAPPO
The programs refer the PPO programs in https://github.com/nikhilbarhate99/PPO-PyTorch. Currently, this program only works for discrete-valued action cases.

To use this module, you need to first write your own environment program in module_env.py, where a sample environment is given. Next, you need to specific the state decomposition function in module_others.py, which is to decompose the common state to individual observations. Then, you can add some key variables in the parser of module_others.py (optional). Finally, you can train your own MAPPO by executing module_train.py. 

Do not modify module_ppo.py. And do use the correct data format when constructing your own state, observation, etc. I have left comments at these positions.