Improving DPOP with function filtering

13 years 28 days ago
Improving DPOP with function filtering
DPOP is an algorithm for distributed constraint optimization which has, as main drawback, the exponential size of some of its messages. Recently, some algorithms for distributed cluster tree elimination have been proposed. They also suffer from exponential size messages. However, using the strategy of cost function filtering, in practice these algorithms obtain important reductions in maximum message size and total communication cost. In this paper, we explain the relation between DPOP and these algorithms, and show how cost function filtering can be combined with DPOP. We present experimental evidence of the benefits of this new approach. Categories and Subject Descriptors I.2 [Artificial Intelligence]: Problem Solving, Search General Terms Algorithms Keywords distributed constraint optimization, agent coordination
Ismel Brito, Pedro Meseguer
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2010
Where ATAL
Authors Ismel Brito, Pedro Meseguer
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