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ECAI 2008

Fast Set Bounds Propagation using BDDs

Conference Paper II. Papers Artificial Intelligence

Abstract

Set bounds propagation is the most popular approach to solving constraint satisfaction problems (CSPs) involving set variables. The use of reduced ordered Binary Decision Diagrams (BDDs) to represent and solve set CSPs is well understood and brings the advantage that propagators for arbitrary set constraints can be built. This can substantially improve solving. The disadvantages of BDDs is that creating and manipulating BDDs can be expensive. In this paper we show how we can perform set bounds propagation using BDDs in a much more efficient manner by generically creating set constraint predicates, and using a marking approach to propagation. The resulting system can be significantly faster than competing approaches to set bounds propagation.

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Context

Venue
European Conference on Artificial Intelligence
Archive span
1982-2025
Indexed papers
5223
Paper id
871640206779851451