Abstract
Local search (LS) and multi-agent-based search (ERA [1]) are stochastic and incomplete procedures for solving a Constraint Satisfaction Problem (CSP). Their performance is seriously undermined by local optima and deadlocks, respectively. Although complete, backtrack (BT) search suffers from thrashing and a high degree of unpredictability in its run-time even within the same problem domain. Further, when the problem is large, the completeness of BT cannot be guaranteed in practice. Gomes et al. [2] proposed to use randomization and rapid restarts (RRR) to overcome the heavy tail behavior of BT. RRR requires the specification of a cutoff value determined from an overall profile of the cost of search for solving the problem. When no such profile is known, the cutoff value is chosen by trial-and-error. Walsh [3] proposed the strategy Randomization and Geometric Restart (RGR), which does not rely on a cost profile but determines the cutoff value as a function of a constant parameter and the number of variables in the problem. Neither RRR nor RGR takes into account the intermediate results of search (i.e., across restarts). We propose an improved restart strategy, Randomization and Dynamic Geometric Restarts (RDGR), which dynamically adapts the value of the cutoff parameter to the results of the search process.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Liu, J., Jing, H., Tang, Y.: Multi-agent oriented constraint satisfaction. Artificial Intelligence 136, 101–144 (2002)
Gomes, C.P., Selman, B., Kautz, H.: Boosting combinatorial search through randomization. In: AAAI 1998, pp. 431–437 (1998)
Walsh, T.: Search in a small world. In: IJCAI 1999, pp. 1172–1177 (1999)
Lim, R., Guddeti, P., Choueiry, B.: An Interactive System for Hiring and Managing Graduate Teaching Assistants. In: Prestigious Applications of Intelligent Systems, ECAI 2004 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Guddeti, V.P. (2004). A Dynamic Restart Strategy for Randomized BT Search. In: Wallace, M. (eds) Principles and Practice of Constraint Programming – CP 2004. CP 2004. Lecture Notes in Computer Science, vol 3258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30201-8_75
Download citation
DOI: https://doi.org/10.1007/978-3-540-30201-8_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23241-4
Online ISBN: 978-3-540-30201-8
eBook Packages: Springer Book Archive