isabella232 / multiagent-competition

Code for the paper "Emergent Complexity via Multi-agent Competition"

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

Competitive Multi-Agent Environments

This repository contains the environments for the paper Emergent Complexity via Multi-agent Competition

Dependencies

Use pip install -r requirements.txt to install dependencies. If you haven't used MuJoCo before, please refer to the installation guide. The code has been tested with the following dependencies:

• Python version 3.6
• OpenAI GYM version 0.9.1 with MuJoCo 1.31 support (use mujoco-py version 0.5.7)
• Tensorflow version 1.1.0
• Numpy version 1.12.1

Installing Package

After installing all dependencies, make sure gym works with support for MuJoCo environments. Next install gym-compete package as:

cd gym-compete
pip install -e .

Check install is successful by coming out of the directory and trying import gym_compete in python console. Some users might require a sudo pip install.

Trying the environments

Agent policies are provided for the various environments in folder agent-zoo. To see a demo of all the environments do:

bash demo_tasks.sh all

To instead try a single environment use:

bash demo_tasks.sh <task>

where <task> is one of: run-to-goal-humans, run-to-goal-ants, you-shall-not-pass, sumo-ants, sumo-humans and kick-and-defend