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@InProceedings{mbs06, 
  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 = {Proceedings of the {ECAI} workshop on Model-Based Systems}, 
  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 = {}, 
  note = 	 {A slightly modified version appears in AAAI 2006.}, 
  OPTnote = 	 {}, 
  OPTannote = 	 {} 
}