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“How do a set of agents optimize over a set of alternatives that have varying degrees of global quality?” Examples l allocating resources l constructing schedules l planning activities Difficulties l No global control/knowledge l Localized communication l Quality guarantees required l Limited time 2

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Adopt AlgorithmAdopt Algorithm for Distributed Constraint OptimizationPragnesh Jay ModiInformation Sciences Institute & Department of Computer Science University of Southern California http://www.isi.edu/~modiDistributed Optimization ProblemHow do a set of agents optimize over a set of alternatives that have varying degrees of global quality? Examples l allocating resources l constructing schedules l planning activities Difficulties l No global control/knowledge l Localized communication l Quality guarantees required l Limited time 2Approachl lConstraint Based Reasoning Distributed Constraint Optimization Problem (DCOP)Adopt algorithm First-ever distributed, asynchronous, optimal algorithm for DCOP Efficient, polynomial-spacelBounded error approximation Principled solution-quality/time-to-solution tradeoffs3Constraint RepresentationWhy constraints for multiagent systems? l Constraints are natural, general, simple Many successful applicationsl lLeverage existing work in AI Constraints Journal, ConferencesAble to model coordination, conflicts, interactions, etcKey advances l Distributed constraints l Constraints have degrees of violation4Distributed Constraint Optimization (DCOP)Given l Variables {x1, x2, , xn}, each assigned to an agent l Finite, discrete domains D1, D2, , Dn, l For each xi, xj, valued constraint fij: Di x Dj N. Goal l Find complete assignment A that minimizes F(A) where,F(

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