Abstract
“Heuristic synergy” refers to improvements in search performance when the decisions made by two or more heuristics are combined. This paper considers combinations based on products and quotients, and a less familiar form of combination based on weighted sums of ratings from a set of base heuristics, some of which result in definite improvements in performance. Then, using recent results from a factor analytic study of heuristic performance, which had demonstrated two main effects of heuristics involving either buildup of contention or look-ahead-induced failure, it is shown that heuristic combinations are effective when they are able to balance these two actions. In addition to elucidating the basis for heuristic synergy (or lack thereof), this work suggests that the task of understanding heuristic search depends on the analysis of these two basic actions.
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References
Bessière, C., Régin, J.-C.: Mac and combined heuristics: Two reasons to forsake fc (and cbj?) on hard problems. In: Freuder, E.C. (ed.) CP 1996. LNCS, vol. 1118, pp. 61–75. Springer, Heidelberg (1996)
Epstein, S.L., Freuder, E.C., Wallace, R., Morozov, A., Samuels, B.: The adaptive constraint engine. In: Van Hentenryck, P. (ed.) CP 2002. LNCS, vol. 2470, pp. 525–540. Springer, Heidelberg (2002)
Wallace, R.J.: Factor analytic studies of csp heuristics. In: van Beek, P. (ed.) CP 2005. LNCS, vol. 3709, pp. 712–726. Springer, Heidelberg (2005)
Harman, H.H.: Modern Factor Analysis, 2nd edn. University of Chicago, Chicago and London (1967)
Lawley, D.N., Maxwell, A.E.: Factor Analysis as a Statistical Method, 2nd edn. Butterworths, London (1971)
Smith, B.M., Grant, S.A.: Trying harder to fail first. In: Proc. Thirteenth European Conference on Artificial Intelligence-ECAI 1998, pp. 249–253. John Wiley & Sons, Chichester (1998)
Geelen, P.A.: Dual viewpoint heuristics for binary constraint satisfaction problems. In: Proc. Tenth European Conference on Artificial Intelligence-ECAI 1992, pp. 31–35 (1992)
Wallace, R.J.: Csp heuristics categorized with factor analytic. In: Creaney, N. (ed.) Proc. Sixteenth Irish Conference on Artificial Intelligence and Cognitive Science, Coleraine, NI, University of Ulster, pp. 213–222 (2005)
Beck, J.C., Prosser, P., Wallace, R.J.: Variable ordering heuristics show promise. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 711–715. Springer, Heidelberg (2004)
Beck, J.C., Prosser, P., Wallace, R.J.: Trying again to fail-first. In: Faltings, B.V., Petcu, A., Fages, F., Rossi, F. (eds.) CSCLP 2004. LNCS, vol. 3419, pp. 41–55. Springer, Heidelberg (2005)
Bessière, C., Zanuttini, B., Fernández, C.: Measuring search trees. In: ECAI 2004 Workshop on Modelling and Solving Problems with Constraints, pp. 31–40 (2004)
Boussemart, F., Hemery, F., Lecoutre, C., Sais, L.: Boosting systematic search by weighting constraints. In: Proc. Sixteenth European Conference on Artificial Intelligence-ECAI 2004, pp. 146–150 (2004)
Gent, I., MacIntyre, E., Prosser, P., Smith, B., Walsh, T.: An empirical study of dynamic variable ordering heuristics for the constraint satisfaction problem. In: Freuder, E.C. (ed.) CP 1996. LNCS, vol. 1118, pp. 179–193. Springer, Heidelberg (1996)
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Wallace, R.J. (2006). Analysis of Heuristic Synergies. In: Hnich, B., Carlsson, M., Fages, F., Rossi, F. (eds) Recent Advances in Constraints. CSCLP 2005. Lecture Notes in Computer Science(), vol 3978. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11754602_6
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DOI: https://doi.org/10.1007/11754602_6
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