ARC-CONSISTENCY FOR CONTINUOUS-VARIABLES

被引:29
作者
FALTINGS, B
机构
[1] Laboratoire d'Intelligence Artificielle, Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, IN-Ecublens
关键词
D O I
10.1016/0004-3702(94)90022-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Davis [1] has investigated the properties of the Waltz propagation algorithm with interval labels in continuous domains. He shows that in most cases the algorithm does not achieve arc-consistency and furthermore is subject to infinite iterations. In this paper, I show that the main reason for Davis' negative results lies in the way he formulates the propagation rule for the Waltz algorithm. For binary constraints, I propose a different propagation rule and show that it guarantees arc-consistency upon quiescence of the propagation. Generalizations to n-ary constraints are possible but involve more complex geometry. Arc-consistency guarantees a minimal network only when the constraint graph is a tree. I show that the new formulation of the propagation algorithm rules out the possibility of infinite iterations for all tree-structured constraint networks, and thus obtain a general and reliable algorithm for arc-consistency in continuous domains.
引用
收藏
页码:363 / 376
页数:14
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