Partially-Observable Grid Environment for Multiple Agents
Pogema is a high-throughput environment for partially observable multi-agent pathfinding tasks (PO-MAPF). Pogema is especially flexible, tunable and scalable environment, which can be tailored to a variety of MAPF settings.
Installation
Just install from PyPI:
pip install pogema==1.0b1
Using Example
import gym
from pogema.grid_config import GridConfig
from pogema.wrappers.multi_time_limit import MultiTimeLimit
from pogema.animation import AnimationMonitor
env = gym.make('Pogema-v0', config=GridConfig(size=16, num_agents=16))
env = MultiTimeLimit(env, max_episode_steps=64)
env = AnimationMonitor(env)
obs = env.reset()
done = [False, ...]
while not all(done):
obs, reward, done, info = env.step([env.action_space.sample() for _ in range(env.config.num_agents)])
Citation
If you use this repository in your research or wish to cite it, please make a reference to our IEEE paper:
@article{skrynnik2021hybrid,
title={Hybrid Policy Learning for Multi-Agent Pathfinding},
author={Skrynnik, Alexey and Yakovleva, Alexandra and Davydov, Vasilii and Yakovlev, Konstantin and Panov, Aleksandr I},
journal={IEEE Access},
volume={9},
pages={126034--126047},
year={2021},
publisher={IEEE}
}
