Making friends on the fly: cooperating with new teammates

DOI10.1016/j.artint.2016.10.005zbMath1392.68411OpenAlexW2535584654MaRDI QIDQ343919

Mohammad Hasan, M. Dambrine

Publication date: 29 November 2016

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2016.10.005

zbMATH Keywords

reinforcement learningmultiagent systemsad hoc teamworkmultiagent cooperationpursuit domainRoboCup soccer

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Artificial intelligence for robotics (68T40) Agent technology and artificial intelligence (68T42)

Related Items (1)

TEAMSTER: model-based reinforcement learning for ad hoc teamwork

Uses Software

• WEKA
• TEXPLORE
• AWESOME

Cites Work

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• Weighted synergy graphs for effective team formation with heterogeneous ad hoc agents
• AWESOME: a general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents
• Collaborative plans for complex group action
• Exploiting Model Equivalences for Solving Interactive Dynamic Influence Diagrams
• Stackelberg vs. Nash in Security Games: An Extended Investigation of Interchangeability, Equivalence, and Uniqueness
• A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)

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