Crafting a robotic swarm pursuit–evasion capture strategy using deep reinforcement learning-Reference-Cited by-同舟云学术

Crafting a robotic swarm pursuit–evasion capture strategy using deep reinforcement learning

Published:2022-05 Issue:2 Volume:27 Page:355-364
ISSN:1433-5298
Container-title:Artificial Life and Robotics
language:en
Short-container-title:Artif Life Robotics

Author:

Wu Charles H.,Sofge Donald A.,Lofaro Daniel M.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,General Biochemistry, Genetics and Molecular Biology

Link

https://link.springer.com/content/pdf/10.1007/s10015-022-00761-y.pdf

Reference18 articles.

1. Andreen D, Jenning P, Napp N, Petersen K (2016) Emergent structures assembled by large swarms of simple robots. In: Posthuman frontiers

2. Awheda MD, Schwartz HM (2016) A decentralized fuzzy learning algorithm for pursuit–evasion differential games with superior evaders. J Intell Robot Syst 83:35–53

3. DeMarco K, Squires E, Day M, Pippin C (2018) Simulating collaborative robots in a massive multi-agent game environment (SCRIMMAGE). In: International symposium on distributed autonomous robotic systems

4. Guadarrama S, Korattikara A, Ramirez O, Castro P, Holly E, Fishman S, Wang K, Gonina E, Wu N, Kokiopoulou E, Sbaiz L, Smith J, Bartók G, Berent J, Harris C, Vanhoucke V, Brevdo E (2018) TF-Agents: a library for reinforcement learning in tensorflow . https://github.com/tensorflow/agents

5. Hüttenrauch M, Sosic A, Neumann G (2018) Deep reinforcement learning for swarm systems. CoRR

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