Multi-Agent-Reinforcement-Learning-Environment

by Bigpig4396

Hello, I pushed some python environments for Multi Agent Reinforcement Learning.

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Multi-Agent-Learning-Environments

Hello, I pushed some python environments for Multi Agent Reinforcement Learning. Some are single agent version that can be used for algorithm testing. I provide documents for each environment, you can check the corresponding pdf files in each directory. Some environments are like:

Multi Agent Soccer Game

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Multi Agent Rescue

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Multi Agent Cleaner

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Multi Agent Move Box

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Multi Agent Catching Pig

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Multi Drones Monitoring

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Multi Agent Maze Running

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Multi Agent Find Treasure

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Firefighters

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Go Together

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Warehouse

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Opposite

image

Dependency

OpenCV, swig

Multi-Agent Environment Standard

Assumption:

Each agent works synchronously.

Member Functions

reset()

rewardlist, done = step(actionlist)

obslist = getobs()

reward_list records the single step reward for each agent, it should be a list like [reward1, reward2,......]. The length should be the same as the number of agents. Each element in the list should be a integer.

done True/False, mark when an episode finishes.

action_list records the single step action instruction for each agent, it should be a list like [action1, action2,...]. The length should be the same as the number of agents. Each element in the list should be a non-negative integer.

obs_list records the single step observation for each agent, it should be a list like [obs1, obs2,...]. The length should be the same as the number of agents. Each element in the list can be any form of data, but should be in same dimension, usually a list of variables or an image.

Typical Monte Carlo Procedures

reset environment by calling reset() get initial observation getobs() for i in range(maxMCiter): get actionlist from controller apply action by step() record returned reward list record new observation by get_obs()

Citation

Cite the environment as:

@misc{shuo2019maenvs,
  Author = {Shuo Jiang},
  Title = {Multi Agent Reinforcement Learning Environments Compilation},
  Year = {2019},
}

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