Gal A. Kaminka's Publications

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Diagnosis of Multi-Robot Coordination Failures Using Distributed CSP Algorithms

Meir Kalech, Gal A. Kaminka, Amnon Meisels, and Yehuda Elmaliach. Diagnosis of Multi-Robot Coordination Failures Using Distributed CSP Algorithms. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06) , 2006.

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Abstract

With increasing deployment of systems involving multiple coordinating agents, there is a growing need for diagnosing coordination failures in such systems. Previous work presented centralized methods for coordination failure diagnosis; however, these are not always applicable, due to the significant computational and communication requirements, and the brittleness of a single point of failure. In this paper we propose a distributed approach to model-based coordination failure diagnosis. We model the coordination between the agents as a constraint graph, and adapt several algorithms from the distributed CSP area, to use as the basis for the diagnosis algorithms. We evaluate the algorithms in extensive experiments with simulated and real Sony Aibo robots and show that in general a trade-off exists between the computational requirements of the algorithms, and their diagnosis results. Surprisingly, in contrast to results in distributed CSPs, the asynchronous backtracking algorithm outperforms stochastic local search in terms of both quality and runtime.

Additional Information

BibTeX

@InProceedings{aaai06meir,
  author = 	 {Meir Kalech and Gal A. Kaminka and Amnon Meisels and Yehuda Elmaliach},
  title = 	 {Diagnosis of Multi-Robot Coordination Failures Using Distributed {CSP} Algorithms},
  OPTcrossref =  {},
  OPTkey = 	 {},
  booktitle = AAAI-06,
  OPTpages = 	 {In press},
  year = 	 {2006},
  abstract = { With increasing deployment of systems involving multiple coordinating agents, there is a growing need 
               for diagnosing coordination failures in such 
               systems. Previous work presented centralized methods
               for coordination failure diagnosis; however, these are
               not always applicable, due to the significant
               computational and communication requirements, and the
               brittleness of a single point of failure. In this paper
               we propose a distributed approach to model-based
               coordination failure diagnosis. We model the
               coordination between the agents as a constraint graph,
               and adapt several algorithms from the distributed CSP
               area, to use as the basis for the diagnosis
               algorithms. We evaluate the algorithms in extensive
               experiments with simulated and real Sony Aibo robots
               and show that in general a trade-off exists between the
               computational requirements of the algorithms, and their
               diagnosis results. Surprisingly, in contrast to results
               in distributed CSPs, the asynchronous backtracking
               algorithm outperforms stochastic local search in terms
               of both quality and runtime.},
  wwwnote = {},
  OPTeditor = 	 {},
  OPTvolume = 	 {},
  OPTnumber = 	 {},
  OPTseries = 	 {},
  OPTaddress = 	 {},
  OPTmonth = 	 {},
  OPTorganization = {},
  OPTpublisher = {},
  OPTnote = 	 {},
  OPTannote = 	 {}
}

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