Multi-Agent algorithms for Multi-Agent Connected Autonomous Driving using MACAD-Gym
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git clone https://github.com/praveen-palanisamy/macad-agents -
Build the MACAD-Agents Docker container:
docker build --rm -f macad-agents/Dockerfile -t macad-agents:latest . -
Run the MACAD-Agents training container:
bash run.shYou can pick from one of the available multi-agent training options:
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To train multiple agents using PPO where the agents communicate/share learned weights, modify the last line in
run.shto look like this:macad-agents:latest python -m macad_agents.rllib.ppo_multiagent_shared_weights.py -
To train multiple agents using IMPALA where the agents communicate/share learned weights, modify the last line in
run.shto look like this:macad-agents:latest python -m macad_agents.rllib.impala_multiagent_shared_weights.py
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If you find this work or MACAD-Gym useful in your research, please cite:
@misc{palanisamy2019multiagent,
title={Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning},
author={Praveen Palanisamy},
year={2019},
eprint={1911.04175},
archivePrefix={arXiv},
primaryClass={cs.LG}
}Citation in other Formats: (Click to View)
| MLA | Palanisamy, Praveen. "Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning." arXiv preprint arXiv:1911.04175 (2019). |
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| APA | Palanisamy, P. (2019). Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning. arXiv preprint arXiv:1911.04175. |
| Chicago | Palanisamy, Praveen. "Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning." arXiv preprint arXiv:1911.04175 (2019). |
| Harvard | Palanisamy, P., 2019. Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning. arXiv preprint arXiv:1911.04175. |
| Vancouver | Palanisamy P. Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning. arXiv preprint arXiv:1911.04175. 2019 Nov 11. |