praveen-palanisamy/macad-gym: MACAD-Gym v0.1.3

MACAD-Gym is a training platform for Multi-Agent Connected Autonomous Driving (MACAD) built on top of the CARLA Autonomous Driving simulator.

MACAD-Gym provides OpenAI Gym-compatible learning environments for various driving scenarios for training Deep RL algorithms in homogeneous/heterogenous, communicating/non-communicating and other multi-agent settings. New environments and scenarios can be easily added using a simple, JSON-like configuration.

Install MACAD-Gym using pip install macad-gym. If you have CARLA installed, you can get going using the following 3 lines of code. If not, follow the Getting started steps.

import gym
import macad_gym
env = gym.make("HomoNcomIndePOIntrxMASS3CTWN3-v0")

# Your agent code here

Any RL library that supports the OpenAI-Gym API can be used to train agents in MACAD-Gym. The MACAD-Agents repository provides sample agents as a starter.

See full README for more information.

• Updated python package version @praveen-palanisamy (#16)
• Added github action for pub to PyPI on creation of a release
• Fixed release-drafter config: yaml value should be str @praveen-palanisamy (#12)
• Added no-response bot @praveen-palanisamy (#11)
• Added release-drafter @praveen-palanisamy (#10)
• Added example for a basic agent script @praveen-palanisamy (#9)
• Added fixed_delta_seconds when running in synchronous mode to allow for proper physics sub-stepping in sync @praveen-palanisamy (#8)
• Fixed typo and dict access in Agent interface example
• Updated README
• Added NeurIPS paper info to README