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DRAMA at the PettingZoo: Dynamically restricted action spaces for multi-agent reinforcement learning frameworks
Oesterle, Michael
;
Grams, Tim
;
Bartelt, Christian
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URL:
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https://hdl.handle.net/10125/107324
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URN:
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urn:nbn:de:bsz:180-madoc-674336
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Document Type:
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Conference or workshop publication
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Year of publication:
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2024
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Book title:
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Proceedings of the 57th Annual Hawaii International Conference on System Sciences, HICSS 2024, Hilton Hawaiian Village Waikiki Beach Resort, Hawaii, USA, January 3-6, 2024
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Page range:
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7810-7819
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Conference title:
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HICSS 2024, 57th Hawaii International Conference on System Sciences
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Location of the conference venue:
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Honolulu, HI
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Date of the conference:
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03.-06.01.2024
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Publisher:
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Bui, Tung X.
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Place of publication:
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Honolulu, HI
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Publishing house:
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Department of IT-Management, Shidler College of Business, University of Hawaii
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ISBN:
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978-0-9981331-7-1
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Publication language:
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English
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Institution:
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Außerfakultäre Einrichtungen > Institut für Enterprise Systems (InES)
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Pre-existing license:
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 Creative Commons Attribution, Non-Commercial, No Derivatives 4.0 International (CC BY-NC-ND 4.0)
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Subject:
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004 Computer science, internet
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Keywords (English):
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multi-agent reinforcement learning , openAI gym , pettingzoo , multi-agent systems , action-space restriction
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Abstract:
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The Agent Environment Cycle (AEC) of PettingZoo has been a major paradigm shift in the implementation of Multi-Agent Reinforcement Learning (MARL) frameworks, providing a unified and concise interface for any kind of multi-agent environment. Based on this model, we propose DRAMA, a principled approach for dynamic action space restrictions. DRAMA can be used to add statically computed physical constraints as well as a self-learning multi-agent governance: It generalizes the idea of action masking to continuous action spaces and self-learning restrictions, while being fully compatible with the AEC implementation of PettingZoo—and, by transitivity, with most major MARL frameworks. In this paper, we provide the theoretical background of restricted multi-agent systems, present an extension of PettingZoo via wrapper classes, and show the potential of our approach for various use cases. By treating dynamic restrictions as an additional player of a multi-agent system, our approach offers novel capabilities and flexibility in handling multi-agent environments and thus serves as a valuable tool for researchers and practitioners in the field.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 | Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt. |
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