Title
Intelligent Backtracking In Clp(R)
Abstract
CLP(ℛ) is a constraint logic programming language in which constraints can be expressed in the domain of real numbers. Computation in this specialized domain gives access to information useful in intelligent backtracking. In this paper, we present an efficient constraint satisfaction algorithm for linear constraints in the real number domain and show that our algorithm directly generates minimal sets of conflicting constraints when failures occur. We demonstrate how information gleaned during constraint satisfaction can be integrated with unification failure analysis. The resulting intelligent backtracking method works in the context of a two-sorted domain, where variables can be bound to either structured terms or real number expressions. We discuss the implementation of backtracking and show examples where the benefit of pruning the search tree outweighs the overhead of failure analysis. © J.C. Baltzer AG, Science Publishers.
Publication Date
1-1-1996
Publication Title
Annals of Mathematics and Artificial Intelligence
Volume
17
Issue
2
Number of Pages
189-211
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/BF02127968
Copyright Status
Unknown
Socpus ID
26444613907 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/26444613907
STARS Citation
Burg, Jennifer J.; Lang, Sheau Dong; and Hughes, Charles E., "Intelligent Backtracking In Clp(R)" (1996). Scopus Export 1990s. 2221.
https://stars.library.ucf.edu/scopus1990/2221