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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.
An earlier version appeared in the Proceedings of the 3rd MONET Workshop on Model-Based Systems
at ECAI-06
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.
@InProceedings{aaai06diag,
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 = {An earlier version appeared in the Proceedings of the 3rd MONET Workshop on Model-Based Systems at ECAI-06},
OPTeditor = {},
OPTvolume = {},
OPTnumber = {},
OPTseries = {},
OPTaddress = {},
OPTmonth = {},
OPTorganization = {},
OPTpublisher = {},
OPTannote = {}
}
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