Abstract
Conventional techniques for the constraint satisfaction problem (CSP) have had considerable success in their applications. However, there are many areas in which the performance of the basic approaches may be improved. These include heuristic ordering of certain tasks performed by the CSP solver, hybrids which combine compatible solution techniques and graph based methods which exploit the structure of the constraint graph representation of a CSP. Also, conventional constraint satisfaction techniques only address problems with hard constraints (i.e. each of which are completely satisfied or completely violated, and all of which must be satisfied by a valid solution). Many real applications require a more flexible approach which relaxes somewhat these rigid requirements. To address these issues various approaches have been developed. This paper attempts a systematic review of them.
Original language | English |
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Pages (from-to) | 269-293 |
Number of pages | 26 |
Journal | Artificial Intelligence Review |
Volume | 15 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1 Jun 2001 |
Keywords
- Constraint satisfaction problems
- Flexible constraint satisfaction
- Graph-based methods
- Heuristics
- Hybrids
- Ill-defined problems