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Ad hoc teamwork is the research problem of designing agents that can collaborate with new teammates without prior coordination.
An empirical study on the practical impact of prior beliefs over policy types
Stefano V. Albrecht, Jacob W. Crandall, and Subramanian Ramamoorthy · 1994
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The evolution of Sharedplans
Barbara J. Grosz and Sarit Kraus · 1999
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Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
Richard S. Sutton, Doina Precup, and Satinder Singh · 1999
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Towards social complexity reduction in multiagent learning: The adhoc approach
Michael Rovatsos and Marco Wolf · 2002
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Coordination and adaptation in impromptu teams
Michael Bowling and Peter McCracken · 2005
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Effects of nonverbal communication on efficiency and robustness in human-robot teamwork
Cynthia Breazeal, Cory D Kidd, Andrea Lockerd Thomaz, Guy Hoffman, and Matt Berlin · 2005
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A framework for sequential planning in multi-agent settings
Piotr J. Gmytrasiewicz and Prashant Doshi · 2005
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Bandit based monte-carlo planning
Levente Kocsis and Csaba Szepesvári · 2006
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A comprehensive survey of multiagent reinforcement learning
Lucian Busoniu, Robert Babuska, and Bart De Schutter · 2007
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Impromptu teams of heterogeneous mobile robots
Ross Mead and Jerry B. Weinberg · 2007
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Ad hoc autonomous agent teams: Collaboration without pre-coordination
Peter Stone, Gal A. Kaminka, Sarit Kraus, and Jeffrey S. Rosenschein · 2010
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Empirical evaluation of ad hoc teamwork in the pursuit domain
Samuel Barrett, Peter Stone, and Sarit Kraus · 2011
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Online planning for ad hoc autonomous agent teams
Feng Wu, Shlomo Zilberstein, and Xiaoping Chen · 2011
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Comparative evaluation of MAL algorithms in a diverse set of ad hoc team problems
Stefano V. Albrecht and Subramanian Ramamoorthy · 2012
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A game-theoretic model and best-response learning method for ad hoc coordination in multiagent systems
Stefano V. Albrecht and Subramanian Ramamoorthy · 2013
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Cooperating with a markovian ad hoc teammate
Doran Chakraborty and Peter Stone · 2013
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Legibility and predictability of robot motion
Anca D Dragan, Kenton CT Lee, and Siddhartha S Srinivasa · 2013
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Modeling uncertainty in leading ad hoc teams
Noa Agmon, Samuel Barrett, and Peter Stone · 2014
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Cooperating with unknown teammates in robot soccer
Samuel Barrett and Peter Stone · 2014
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Communicating with unknown teammates
Samuel Barrett, Noa Agmon, Noam Hazon, Sarit Kraus, and Peter Stone · 2014
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Influencing a Flock via Ad Hoc Teamwork
Katie Genter and Peter Stone · 2014
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Active behavior recognition in beyond visual range air combat
Ron Alford, Hayley Borck, and Justin Karneeb · 2015
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Determining placements of influencing agents in a flock
Katie Genter, Shun Zhang, and Peter Stone · 2015
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Tuning belief revision for coordination with inconsistent teammates
Trevor Sarratt · 2015
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Belief and truth in hypothesised behaviours
Stefano V. Albrecht, Jacob W. Crandall, and Subramanian Ramamoorthy · 2016
Cited alongside, same era.
Making friends on the fly: Cooperating with new teammates
Samuel Barrett, Avi Rosenfeld, Sarit Kraus, and Peter Stone · 2016
Cited alongside, same era.
Individual planning in open and typed agent systems
Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, and Leenkiat Soh · 2016
Cited alongside, same era.
Plan-based reward shaping for multi-agent reinforcement learning
Sam Devlin and Daniel Kudenko · 2016
Cited alongside, same era.
Adding influencing agents to a flock
Katie Genter and Peter Stone · 2016
Cited alongside, same era.
Ad hoc teamwork by learning teammates’ task
Francisco S. Melo and Alberto Sardinha · 2016
Cited alongside, same era.
Towards continual reinforcement learning: A review and perspectives
Khimya Khetarpal, Matthew Riemer, Irina Rish, and Doina Precup · 2020
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A penny for your thoughts: The value of communication in ad hoc teamwork
Reuth Mirsky, William Macke, Andy Wang, Harel Yedidsion, and Peter Stone · 2020
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Active goal recognition
Maayan Shvo and Sheila A McIlraith · 2020
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OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning
Alexander Vezhnevets, Yuhuai Wu, Maria Eckstein, Rémi Leblond, and Joel Z. Leibo · 2020
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Learning latent representations to influence multi-agent interaction
Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, and Dorsa Sadigh · 2020
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Reasoning about hypothetical agent behaviours and their parameters
Stefano V. Albrecht and Peter Stone · 2017
Cited alongside, same era.
Special issue on multiagent interaction without prior coordination: Guest editorial
Stefano V. Albrecht, Somchaya Liemhetcharat, and Peter Stone · 2017
Cited alongside, same era.
Three years of the RoboCup standard platform league drop-in player competition: Creating and maintaining a large scale ad hoc teamwork robotics competition
Katie Genter, Tim Laue, and Peter Stone · 2017
Cited alongside, same era.
Allocating training instances to learning agents for team formation
Somchaya Liemhetcharat and Manuela Veloso · 2017
Cited alongside, same era.
Autonomous agents modelling other agents: A comprehensive survey and open problems
Stefano V. Albrecht and Peter Stone · 2018
Cited alongside, same era.
An efficient, generalized Bellman update for cooperative inverse reinforcement learning
Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac, Dylan Hadfield-Menell, Stuart Russell, and Anca D. Dragan · 2018
Cited alongside, same era.
Kalesha Bullard, Douwe Kiela, Franziska Meier, Joelle Pineau, and Jakob Foerster · 2021
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A review of physics simulators for robotic applications
Jack Collins, Shelvin Chand, Anthony Vanderkop, and David Howard · 2021
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Off-belief learning
Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, Noam Brown, and Jakob Foerster · 2021
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Scalable evaluation of multi-agent reinforcement learning with Melting Pot
Joel Z. Leibo, Edgar A. Dueñez-Guzman, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, and Thore Graepel · 2021
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Individualized mutual adaptation in human-agent teams
Huao Li, Tianwei Ni, Siddharth Agrawal, Fan Jia, Suhas Raja, Yikang Gui, Dana Hughes, Michael Lewis, and Katia Sycara · 2021
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Trajectory diversity for zero-shot coordination
Andrei Lupu, Brandon Cui, Hengyuan Hu, and Jakob Foerster · 2021
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Expected value of communication for planning in ad hoc teamwork
William Macke, Reuth Mirsky, and Peter Stone · 2021
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Prevention and resolution of conflicts in social navigation–a survey
Reuth Mirsky, Xuesu Xiao, Justin Hart, and Peter Stone · 2021
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Open-ended learning leads to generally capable agents
Open-Ended Learning Team, Adam Stooke, Anuj Mahajan, Catarina Barros, Charlie Deck, Jakob Bauer, Jakub Sygnowski, Maja Trebacz, Max Jaderberg, Michaël Mathieu, Nat McAleese, Nathalie Bradley-Schmieg, Nathaniel Wong, Nicolas Porcel, Roberta Raileanu, Steph Hughes-Fitt, Valentin Dalibard, and Wojciech Marian Czarnecki · 2021
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Local information agent modelling in partially-observable environments
Georgios Papoudakis, Filippos Christianos, and Stefano V. Albrecht · 2021
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Towards open ad hoc teamwork using graph-based policy learning
Arrasy Rahman, Niklas Höpner, Filippos Christianos, and Stefano V. Albrecht · 2021
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Artificial Intelligence: A Modern Approach
Stuart J. Russell and Peter Norvig · 2021
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Ad hoc teamwork in the presence of non-stationary teammates
Pedro M. Santos, João G. Ribeiro, Alberto Sardinha, and Francisco S. Melo · 2021
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Reasoning about human behavior in ad hoc teamwork
Jennifer Suriadinata, William Macke, Reuth Mirsky, and Peter Stone · 2021
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Too many cooks: Bayesian inference for coordinating multi-agent collaboration
Rose E. Wang, Sarah A. Wu, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, and Max Kleiman-Weiner · 2021
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Deep interactive Bayesian reinforcement learning via meta-learning
Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, and Katja Hofmann · 2021
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Towards robust ad hoc teamwork agents by creating diverse training teammates
Arrasy Rahman, Elliot Fosong, Ignacio Carlucho, and Stefano V. Albrecht · 2022
Closest in time.
Assisting Unknown Teammates in Unknown Tasks: Ad Hoc Teamwork under Partial Observability
João G. Ribeiro, Cassandro Martinho, Alberto Sardinha, and Francisco S. Melo · 2022
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