Finite-time Analysis of the Multiarmed Bandit Problem
Machine Learning
Planning, learning and coordination in multiagent decision processes
TARK '96 Proceedings of the 6th conference on Theoretical aspects of rationality and knowledge
Combining online and offline knowledge in UCT
Proceedings of the 24th international conference on Machine learning
Emerging coordination in infinite team Markov games
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Formal models and algorithms for decentralized decision making under uncertainty
Autonomous Agents and Multi-Agent Systems
Essentials of Game Theory: A Concise, Multidisciplinary Introduction
Essentials of Game Theory: A Concise, Multidisciplinary Introduction
Sequential optimality and coordination in multiagent systems
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Continual planning and acting in dynamic multiagent environments
Autonomous Agents and Multi-Agent Systems
To teach or not to teach?: decision making under uncertainty in ad hoc teams
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Online planning for multi-agent systems with bounded communication
Artificial Intelligence
Empirical evaluation of ad hoc teamwork in the pursuit domain
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
The complexity of decentralized control of Markov decision processes
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Bandit based monte-carlo planning
ECML'06 Proceedings of the 17th European conference on Machine Learning
Comparative evaluation of MAL algorithms in a diverse set of ad hoc team problems
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
An analysis framework for ad hoc teamwork tasks
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Cooperating with a markovian ad hoc teammate
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Teaching and leading an ad hoc teammate: Collaboration without pre-coordination
Artificial Intelligence
Weighted synergy graphs for effective team formation with heterogeneous ad hoc agents
Artificial Intelligence
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We propose a novel online planning algorithm for ad hoc team settings--challenging situations in which an agent must collaborate with unknown teammates without prior coordination. Our approach is based on constructing and solving a series of stage games, and then using biased adaptive play to choose actions. The utility function in each stage game is estimated via Monte-Carlo tree search using the UCT algorithm. We establish analytically the convergence of the algorithm and show that it performs well in a variety of ad hoc team domains.