An analysis framework for ad hoc teamwork tasks

In multiagent team settings, the agents are often given a protocol for coordinating their actions. When such a protocol is not available, agents must engage in ad hoc teamwork to effectively cooperate with one another. A fully general ad hoc team agent needs to be capable of collaborating with a wide range of potential teammates on a varying set of joint tasks. This paper presents a framework for analyzing ad hoc team problems that sheds light on the current state of research and suggests avenues for future research. In addition, this paper shows how previous theoretical results can aid ad hoc agents in a set of testbed domains.

[1]  Brett Browning,et al.  Dynamically formed heterogeneous robot teams performing tightly-coordinated tasks , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[2]  Kagan Tumer,et al.  Robot coordination with ad-hoc team formation , 2010, AAMAS.

[3]  Sandip Sen,et al.  Teaching new teammates , 2006, AAMAS '06.

[4]  Sarit Kraus,et al.  Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination , 2010, AAAI.

[5]  Milind Tambe,et al.  Towards Flexible Teamwork , 1997, J. Artif. Intell. Res..

[6]  Sarit Kraus,et al.  Collaborative Plans for Complex Group Action , 1996, Artif. Intell..

[7]  Sarit Kraus,et al.  Teamwork with Limited Knowledge of Teammates , 2013, AAAI.

[8]  Faruk Polat,et al.  Multi-agent real-time pursuit , 2009, Autonomous Agents and Multi-Agent Systems.

[9]  Edmund H. Durfee,et al.  Recursive Agent Modeling Using Limited Rationality , 1995, ICMAS.

[10]  Victor R. Lesser,et al.  Designing a Family of Coordination Algorithms , 1997, ICMAS.

[11]  M. Benda,et al.  On Optimal Cooperation of Knowledge Sources , 1985 .

[12]  Feng Wu,et al.  Online Planning for Ad Hoc Autonomous Agent Teams , 2011, IJCAI.

[13]  Peter Stone,et al.  Leading a Best-Response Teammate in an Ad Hoc Team , 2009, AMEC/TADA.

[14]  Vincent Conitzer,et al.  AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents , 2003, Machine Learning.

[15]  Yukinori Kakazu,et al.  An approach to the pursuit problem on a heterogeneous multiagent system using reinforcement learning , 2003, Robotics Auton. Syst..

[16]  Sarit Kraus,et al.  Empirical evaluation of ad hoc teamwork in the pursuit domain , 2011, AAMAS.

[17]  Ronen I. Brafman,et al.  On Partially Controlled Multi-Agent Systems , 1996, J. Artif. Intell. Res..

[18]  Sarit Kraus,et al.  To teach or not to teach?: decision making under uncertainty in ad hoc teams , 2010, AAMAS.

[19]  Manuela M. Veloso,et al.  Multiagent Systems: A Survey from a Machine Learning Perspective , 2000, Auton. Robots.

[20]  Ming Li,et al.  Soft Control on Collective Behavior of a Group of Autonomous Agents By a Shill Agent , 2006, J. Syst. Sci. Complex..

[21]  Peter Stone,et al.  Empowerment for continuous agent—environment systems , 2011, Adapt. Behav..