Abstract
We study experimentally the effect of dynamic learning of the problem topographic characteristics on stochastic search.
Keywords
- Constraint Satisfaction
- Constraint Satisfaction Problem
- Unary Constraint
- Successful Attempt
- Stochastic Search
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Naveh, Y.: Stochastic solver for constraint satisfaction problems with learning of high-level characteristics of the problem topography. In: Proceedings of the 1st International Workshop on Local Search Techniques in Constraint Satisfaction (LSCS 2004). (2004)
Naveh, Y., Rimon, M., Jaeger, I., Katz, Y., Vinov, M., Marcus, E., Shurek, G.: Constraint-based random stimuli generation for hardware verification. AI Magazine 28, 13–30 (2007)
Sabato, S., Naveh, Y.: Preprocessing expression-based constraint satisfaction problems for stochastic local search. In: Van Hentenryck, P., Wolsey, L.A. (eds.) CPAIOR 2007. LNCS, vol. 4510, pp. 244–259. Springer, Heidelberg (2007)
Burke, E.K., Kendall, G.N., Newall, J., Hart, E., Ross, P., Schulenburg, S.: Hyper-Heuristics: An Emerging Direction in Modern Search Technology. In: Handbook of Meta-Heuristics, pp. 457–474. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Naveh, Y. (2008). Guiding Stochastic Search by Dynamic Learning of the Problem Topography. In: Perron, L., Trick, M.A. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2008. Lecture Notes in Computer Science, vol 5015. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68155-7_36
Download citation
DOI: https://doi.org/10.1007/978-3-540-68155-7_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68154-0
Online ISBN: 978-3-540-68155-7
eBook Packages: Computer ScienceComputer Science (R0)