Intelligent search strategies based on adaptive Constraint Handling Rules

Theory and Practice of Logic Programming

Volumn 5, Issue 4-5, 2005, Pages 567-594

  Wolf, Armin ^a  

^a FRAUNHOFER FIRST   (Germany)

Author keywords

Conflict directed backjumping; Dynamic backtracking; Intelligent search; Rule based constraint handling; SAT problems

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUTONOMOUS AGENTS; KNOWLEDGE ACQUISITION; LINEAR PROGRAMMING; MATHEMATICAL MODELS; PROBLEM SOLVING; SENSORS;

CONFLICT-DIRECTED BACKJUMPING; DYNAMIC BACKTRACKING; INTELLIGENT SEARCH; RULE-BASED CONSTRAINT HANDLING; SAT PROBLEMS;

CONSTRAINT THEORY;

EID: 22944477760     PISSN: 14710684     EISSN: None     Source Type: Journal    
DOI: 10.1017/S1471068405002383     Document Type: Article

References (25)

1. BAKER, A. B. 1994. The hazards of fancy backtracking. In Proceedings of the Twelfth National Conference on Artificial Intelligence - AAAI'94, 288-293.
2. BLIEK, C. 1998. Generalizing partial order and dynamic backtracking. In Proceedings of the Fifth National Conference on Artificial Intelligence - AAAI'98, 319-325.
3. BRUYNOOGHE, M. 2004. Enhancing a search algorithm to perform intelligent backtracking. Theory and Practice of Logic Programming 4, 3, 371-380.
4. DAVIS, M. AND PUTNAM, H. 1960. A computing procedure for quantification theory. Journal of the ACM 7, 3, 201-215.
5. FRÜHWIRTH, T. 1995. Constraint Handling Rules. In Constraint Programming: Basics and Trends: Lecture Notes in Computer Science 910, A. Podelski, Ed. Springer-Verlag, 90-107.
6. FRÜHWIRTH, T. 1998. Theory and practice of Constraint Handling Rules. Journal of Logic Programming 37, 95-138.
7. FRÜHWIRTH, T. AND BRISSET, P. 1995. High-level implementations of constraint handling rules. Technical report ECRC-TR-95-20, ECRC.
8. GINSBERG, M. L. 1993. Dynamic backtracking. Journal of Artificial Intelligence Research 1, 25-46.
9. GINSBERG, M. L. AND MCALLESTER, D. A. 1994. GSAT and dynamic backtracking. Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning, J. Doyle, E. Sandewall and P. Torasso, Eds. Morgan Kaufmann, San Francisco, CA, 226-237.
10. GIUNCHIGLIA, E., NARIZZANO, M. AND TACCHELLA, A. 2001. Backjumping for quantified boolean logic satisfiability. Proceedings of the 17th International Joint Conference on Artificial Intelligence - IJCAI 2001, B. Nebel, Ed. Vol. 1. Seattle, Washington, USA, 275-281.
11. HOLZBAUR, C. 1990. Specification of constraint based inference mechanism through extended unification. PhD thesis, Department of Medical Cybernetics & AI, University of Vienna.
12. HOLZBAUR, C. AND FRÜHWIRTH, T. 2000. A Prolog Constraint Handling Rules compiler and runtime system. Applied Artificial Intelligence 14, 4 (April), 369-388.
13. IWAMA, K., MIYANO, E. AND ASAHIRO, Y. 1996. Random generation of test instances with controlled attributes. In Cliques, Coloring, and Satisfiability. DIM ACS Series in Discrete Mathematics and Theoretical Computer Science, vol. 26. American Mathematical Society, 377-394.
14. JUSSIEN, N. 2001. e-constraints: explanation-based constraint programming. Proceedings of the CP 2001 Workshop on User Interaction in Constraint Satisfaction. (Also available as research report 01-05-INFO, École des Mines de Nantes, 2001.)
15. JUSSIEN, N., DEBRUYNE, R. AND BOIZUMAULT, P. 2000. Maintaining arc-consistency within dynamic backtracking. Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming CP 2000, R. Dechter, Ed. Number 1894 in Lecture Notes in Computer Science. Springer-Verlag, 249-261.
16. LYNCE, I. AND MARQUES-SILVA, J. 2002. Building state-of-the-art SAT solvers. Proceedings of the European Conference on Artificial Intelligence ECAI'02, 166-170.
17. MARRIOTT, K. AND STUCKEY, P. J. 1998. Programming with Constraints: An Introduction. MIT Press.
18. MÜLLER, H. 2004. Analyse und Entwicklung von intelligenten abhängigkeitsgesteuerten Suchverfahren für einen Java-basierten Constraintlöser. MS thesis, Technische Universität Berlin.
19. PROSSER, P. 1993. Hybrid algorithms for the constraint satisfaction problem. Computational Intelligence 9, 3, 268-299. (Also available as technical report AISL-46-91, Stratchclyde, 1991.)
20. PROSSER, P. 1995. MAC-CBJ: maintaining arc consistency with conflict-directed backjumping. Research report, Department of Computer Science, University of Strathclyde, Glasgow G1 1XH, Scotland.
21. SCHMAUSS, M. 1999. An implementation of CHR in Java. MS thesis, Ludwig Maximilians Universität München, Institut für Informatik.
22. VERFAILLIE, G. AND SCHIEX, T. 1994. Dynamic backtracking for dynamic constraint satisfaction problems. ECAI'94 Workshop on Constraint Satisfaction Issues Raised by Practical Applications, T. Schiex and C. Bessiére, Eds. Amsterdam, Netherlands, 1-8.
23. WOLF, A. 1999. Adaptive Constraintverarbeitung mit Constraint-Handling-Rules - Ein allgemeiner Ansatz zur Lösung dynamischer Constraint-Probleme. Disserationen zur Künstlichen Intelligenz (DISKI), vol. 219. Infix Verlag.
24. WOLF, A. 2001 a. Adaptive constraint handling with CHR in Java. Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming - CP 2007, T. Walsh, Ed. Number 2239 in Lecture Notes in Computer Science. Springer-Verlag, 256-270.
25. WOLF, A. 2001b. Attributed variables for dynamic constraint solving. The Proceedings of the 14th International Conference on Applications of Prolog, INAP'01, I. O. Commitee, Ed. Prolog Association of Japan, University of Tokyo, Tokyo, Japan, 211-219.