Summarizing CSP hardness with continuous probability distributions

Summarizing CSP hardness with continuous probability distributions (1997)

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by Daniel Frost , Irina Rish , Lluis Vila

Venue:	In Proceedings of the 14th National Conference on AI
Citations:	28 - 2 self

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Datum	Value	Source
TITLE	Summarizing CSP hardness with continuous probability distributions	INFERENCE
AUTHOR NAME	Daniel Frost	user correction - Legacy Corrections
AUTHOR AFFIL	Dept. of Information and Computer Science; University of California, Irvine	user correction - Legacy Corrections
AUTHOR ADDR	CA 92717-3425	user correction - Legacy Corrections
AUTHOR NAME	Irina Rish	user correction - Legacy Corrections
AUTHOR AFFIL	Dept. of Information and Computer Science; University of California, Irvine	user correction - Legacy Corrections
AUTHOR ADDR	CA 92717-3425	user correction - Legacy Corrections
AUTHOR NAME	Lluis Vila	user correction - Legacy Corrections
ABSTRACT	We present empirical evidence that the distribution of effort required to solve CSPs randomly generated at the 50% satisfiable point, when using a backtracking algorithm, can be approximated by two standard families of continuous probability distribution functions. Solvable problems can be modelled by the Weibull distribution, and unsolvable problems by the lognormal distribution. These distributions fit equally well over a variety of backtracking based algorithms. 1. Introduction Several key developments in the 1990's have contributed to the advancement of empirical research on CSP algorithms, to the extent that the field may even be called an experimental science. Striking increases in computer power and decreases in cost, coupled with the general adoption of C as the programming language of choice, have made it possible for the developer of a new algorithm or heuristic to test it on large numbers of random instances. Another important advance was the recognition of the "50% satisfi...	user correction - Legacy Corrections
YEAR	1997	INFERENCE
VENUE	In Proceedings of the 14th National Conference on AI	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	327--333	INFERENCE
CITATIONS	19 found	ParsCit 1.0