On the complexity of learning to cooperate in populations of socially rational agents

Loftin, R. orcid.org/0000-0001-9888-178X, Bandyopadhyay, S. and Çelikok, M.M. (2025) On the complexity of learning to cooperate in populations of socially rational agents. In: Vorobeychik, Y., Das, S. and Nowé, A., (eds.) Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS2025). 24th International Conference on Autonomous Agents and Multiagent Systems, 19-23 May 2025, Detroit, Michigan, USA. International Foundation for Autonomous Agents and Multiagent Systems (AAMAS) , pp. 233-241. ISBN 9798400714269

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Vorobeychik, Y.
  • Das, S.
  • Nowé, A.
Copyright, Publisher and Additional Information:

© 2025 International Foundation for Autonomous Agents and Multiagent Systems. This work is licensed under a Creative Commons Attribution International 4.0 License - https://creativecommons.org/licenses/by/4.0/

Keywords: Social Cooperation; Rational Agents; Upper Bound; Stackelberg Equilibria; Imitation Learning; Reinforcement Learning, Offline; Replicator Dynamics
Dates:
  • Accepted: 19 December 2024
  • Published (online): 19 May 2025
  • Published: 19 May 2025
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 21 Feb 2025 09:51
Last Modified: 30 May 2025 09:31
Published Version: https://www.ifaamas.org/Proceedings/aamas2025/
Status: Published online
Publisher: International Foundation for Autonomous Agents and Multiagent Systems (AAMAS)
Refereed: Yes
Related URLs:
Open Archives Initiative ID (OAI ID):

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