Learning to coordinate without sharing information
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Collaborative plans for complex group action
Artificial Intelligence
The dynamics of reinforcement learning in cooperative multiagent systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Artificial Intelligence - Special issue on Robocop: the first step
ÜberSim: a multi-robot simulator for robot soccer
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Journal of Artificial Intelligence Research
Impromptu teams of heterogeneous mobile robots
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Leading ad hoc agents in joint action settings with multiple teammates
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
Role selection in ad hoc teamwork
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Cooperating with a markovian ad hoc teammate
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Ad hoc coordination in multiagent systems with applications to human-machine interaction
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
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Coordinating a team of autonomous agents is one of the major challenges in building effective multiagcnt systems. Many techniques have been devised for this problem. and coordinated teamwork has been demonstrated even in highly dynamic and adversarial environments. A key assumption of these techniques. though. is that the team members are developed together as a whole. In many multi agent scenarios. this assumption is violated. We study the problem of coordination in impromptu teams, where a team is composed of independent agents each unknown to the others. The team members have their own skills. models. strategies. and coordination mechanisms. and no external organization is imposed upon them. In particular. we propose two techniques. one adaptive and one predictive. for coordinating a single agent that joins an unknown team of existing agents. We experimentally evaluate these mechanisms in the robot soccer domain, while introducing useful baselines for evaluating the performance of impromptu teams. We show some encouraging success while demonstrating this is a very fertile area of research.