Macad-gym

- Update `Pedestrian -> Walker` in actor type
- Yaml -> yml
- Update version number in docs conf
- Add env.close() to properly cleanup sim server proc praveen-palanisamy (25)
- Improve code maintainability praveen-palanisamy (18)
- Added py pkg badges to README praveen-palanisamy (17)

- 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

[MACAD-Gym](https://arxiv.org/abs/1911.04175) 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.

Quick Start

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](getting-started).

python
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](https://github.com/praveen-palanisamy/macad-agents) repository provides sample agents as a starter.

See full [README](https://github.com/praveen-palanisamy/macad-gym) for more information.