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Theoretical Computer Science
Volume 249, Issue 2, 28 October 2000, Pages 243-263
 
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doi:10.1016/S0304-3975(00)00061-X    
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Copyright © 2000 Elsevier Science B.V. All rights reserved.

Complexity-theoretic models of phase transitions in search problems*1

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Paul E. DunneCorresponding Author Contact Information, E-mail The Corresponding Author, Alan GibbonsE-mail The Corresponding Author and Michele ZitoE-mail The Corresponding Author

Department of Computer Science, University of Liverpool, P.O. Box 147, Chadwick Building, Liverpool L69 7ZF, UK


Available online 6 November 2000.

Abstract

In recent years, numerous studies have observed that many hard combinatorial decision problems exhibit behaviour described as a ‘phase-transition’. This is the phenomenon whereby typical instances of a problem display a dramatic shift in certain characteristics as some parameter of the instances is varied. Such characteristics include the likelihood of an instance having a solution and the time taken by a search algorithm. The apparent pervasiveness of phase-transitions in hard combinatorial search problems has led to contrasting claims being advanced concerning to what extent all NP-complete problems exhibit phase-transitions. The established importance of exploiting phase-transition effects in the design of search heuristics provides a strong motivation for assessing how valid such claims may be. In this paper we argue that questions concerning the generality of phase-transition phenomena are, at present, ill-defined. In order to address this difficulty, we propose and examine rigorous complexity-theoretic models of the statement ‘the decision problem D has a phase-transition’. Within these models it is proved that for certain ‘natural’ definitions contrasting results about phase-transition behaviour can be proved.

Author Keywords: Computational complexity; Phase-transitions; Search problems

*1 This work reported in this paper was carried out with support from EPSRC grant GRL/L/77089.

Corresponding Author Contact Information Corresponding author; email: ped@csc.liv.ac.uk


Theoretical Computer Science
Volume 249, Issue 2, 28 October 2000, Pages 243-263
 
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