https://github.com/openai/robosumo

Code for the paper "Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments"
https://github.com/openai/robosumo

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Code for the paper "Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments"

• Host: GitHub
• URL: https://github.com/openai/robosumo
• Owner: openai
• Created: 2017-10-11T03:40:10.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2023-04-13T09:24:42.000Z (over 1 year ago)
• Last Synced: 2024-09-27T06:21:24.127Z (3 months ago)
• Topics: paper
• Language: Python
• Homepage: https://arxiv.org/abs/1710.03641
• Size: 16.2 MB
• Stars: 299
• Watchers: 21
• Forks: 80
• Open Issues: 5
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-deep-rl - OpenAI RoboSumo - A set of competitive multi-agent environments used in the paper Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. (Environments)

README

        
**Status:** Archive (code is provided as-is, no updates expected)

RoboSumo

========

This repository contains a set of competitive multi-agent environments used in the paper [Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments](https://arxiv.org/abs/1710.03641).

    

        

        

    

## Installation

RoboSumo depends on `numpy`, `gym`, and `mujoco_py>=1.5` (if you haven't used MuJoCo before, please refer to [the installation guide](https://github.com/openai/mujoco-py)).

Running demos with pre-trained policies additionally requires `tensorflow>=1.1.0` and `click`.

The requirements can be installed via [pip](https://pypi.python.org/pypi/pip) as follows:

```bash

$ pip install -r requirements.txt

```

To install RoboSumo, clone the repository and run `pip install`:

```bash

$ git clone https://github.com/openai/robosumo

$ cd robosumo

$ pip install -e .

```

## Demos

You can run demos of the environments using `demos/play.py` script:

```bash

$ python demos/play.py

```

The script allows you to select different opponents as well as different policy architectures and versions for the agents.

For details, please refer to the help:

```bash

$ python demos/play.py --help

Usage: play.py [OPTIONS]

Options:

  --env TEXT                    Name of the environment.  [default: RoboSumo-Ant-vs-Ant-v0]

  --policy-names [mlp|lstm]...  Policy names.  [default: mlp, mlp]

  --param-versions INTEGER...   Policy parameter versions.  [default: 1, 1]

  --max_episodes INTEGER        Number of episodes.  [default: 20]

  --help                        Show this message and exit.

```