Status: Archive (code is provided as-is, no updates expected)
This repository contains the environments for the paper Emergent Complexity via Multi-agent Competition
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
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
.
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