Decentralized Multi-agent Formation Control via Deep Reinforcement Learning

Aniket Gutpa, Raghava Nallanthighal

Abstract

Multi-agent formation control has been a much-researched topic and while several methods from control theory exist, they require astute expertise to tune properly which is highly resource-intensive and often fails to adapt properly to slight changes in the environment. This paper presents an end-to-end decentralized approach towards multi-agent formation control with the information available from onboard sensors by using a Deep Reinforcement learning framework. The proposed method directly utilizes the raw sensor readings to calculate the agent’s movement velocity using a Deep Neural Network. The approach utilizes Policy gradient methods to generalize efficiently on various simulation scenarios and is trained over a large number of agents. We validate the performance of the learned policy using numerous simulated scenarios and a comprehensive evaluation. Finally, the performance of the learned policy is demonstrated in new scenarios with non-cooperative agents that were not introduced during the training process.

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Paper Citation


in Harvard Style

Gutpa A. and Nallanthighal R. (2021). Decentralized Multi-agent Formation Control via Deep Reinforcement Learning.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-484-8, pages 289-295. DOI: 10.5220/0010241302890295


in Bibtex Style

@conference{icaart21,
author={Aniket Gutpa and Raghava Nallanthighal},
title={Decentralized Multi-agent Formation Control via Deep Reinforcement Learning},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2021},
pages={289-295},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010241302890295},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Decentralized Multi-agent Formation Control via Deep Reinforcement Learning
SN - 978-989-758-484-8
AU - Gutpa A.
AU - Nallanthighal R.
PY - 2021
SP - 289
EP - 295
DO - 10.5220/0010241302890295