Ordered Multi-variable Multi-constrained Distributed Constraint Optimization Framework

Applying distributed constraint optimization problem (DCOP) solution techniques to domains such as service-oriented agent networks can violate key limiting assumptions behind standard DCOP formulations. We extend the multi-constrained (MC-) DCOP to model problems where each agent controls multiple v...

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Vydané v:2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Ročník 2; s. 379 - 382
Hlavní autori: Portway, Christopher, Durfee, Edmund H
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.08.2010
Predmet:
Artificial intelligence
Bismuth
Constraint optimization
Distributed algorithms
Joints
Limiting
Planning
Runtime
System-on-a-chip
Temporal reasoning
Uncertainty
ISBN:9781424484829, 1424484820
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Shrnutí:Applying distributed constraint optimization problem (DCOP) solution techniques to domains such as service-oriented agent networks can violate key limiting assumptions behind standard DCOP formulations. We extend the multi-constrained (MC-) DCOP to model problems where each agent controls multiple variables, calling this multi-variable (MV-) MC-DCOP. The MV-MC-DCOP formulation abstracts away some problem details including those about task ordering, so we have developed an ordered variation O-MV-MC-DCOP. We empirically show that the [O-]MV-MC-DCOP approach can fruitfully prune the space of joint policies that service-oriented agents would otherwise explore.
ISBN:9781424484829
1424484820
DOI:10.1109/WI-IAT.2010.285