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The satisfiability threshold for randomly generated binary constraint satisfaction problems

2006
*
Random structures & algorithms (Print)
*

We study two natural models of

doi:10.1002/rsa.20118
fatcat:zbvvznt7b5gt3musk2mjaupbf4
*randomly**generated**constraint**satisfaction**problems*. ... We determine how quickly*the*domain size must grow with n to ensure that these models are robust in*the*sense that they exhibit a non-trivial*threshold*of*satisfiability*, and we determine*the*asymptotic ... Introduction*The**Constraint**Satisfaction**Problem*(CSP) is a broadly studied*generalization*of k-SAT. ...##
###
The Satisfiability Threshold for Randomly Generated Binary Constraint Satisfaction Problems
[chapter]

2003
*
Lecture Notes in Computer Science
*

We study two natural models of

doi:10.1007/978-3-540-45198-3_24
fatcat:uhvyu3miu5dspo277jnpe25jke
*randomly**generated**constraint**satisfaction**problems*. ... We determine how quickly*the*domain size must grow with n to ensure that these models are robust in*the*sense that they exhibit a non-trivial*threshold*of*satisfiability*, and we determine*the*asymptotic ... Introduction*The**Constraint**Satisfaction**Problem*(CSP) is a broadly studied*generalization*of k-SAT. ...##
###
Page 7844 of Mathematical Reviews Vol. , Issue 2003j
[page]

2003
*
Mathematical Reviews
*

O.] (3-TRNT-C; Toronto, ON) A probabilistic analysis of

*randomly**generated**binary**constraint**satisfaction**problems*. Theoret. Comput. Sci. 290 (2003), no. 3, 1815-1828. ... Summary: “Solving non-*binary**constraint**satisfaction**problems*, a crucial challenge today, can be tackled in two different ways: translating*the*non-*binary**problem*into an equivalent*binary*one, or extending ...##
###
NAIS: A Calibrated Immune Inspired Algorithm to Solve Binary Constraint Satisfaction Problems
[chapter]

2007
*
Lecture Notes in Computer Science
*

*The*tests were carried out using random

*generated*

*binary*

*constraint*

*satisfaction*

*problems*on

*the*transition phase where are

*the*hardest

*problems*. ... We have calibrated our algorithm using Relevance Estimation and Value Calibration (REVAC), that is a new technique, recently introduced to find

*the*parameter values

*for*evolutionary algorithms. ...

*Binary*

*Constraint*

*Satisfaction*

*Problems*

*For*simplicity we restrict our attention here to

*binary*CSPs, where

*the*

*constraints*involve two variables.

*Binary*

*constraints*are

*binary*relations. ...

##
###
Random constraint satisfaction: Easy generation of hard (satisfiable) instances

2007
*
Artificial Intelligence
*

Li, Exact phase transitions in random

doi:10.1016/j.artint.2007.04.001
fatcat:ru3xqka5vff7rbn2tesiptyosm
*constraint**satisfaction**problems*, Journal of Artificial Intelligence Research 12 (2000) 93-103; K. Xu, W. ... In that case, a*threshold*point can be precisely located and all instances have*the*guarantee to be hard at*the**threshold*, i.e., to have an exponential tree-resolution complexity. ... Acknowledgements We would like to thank*the*AIJ anonymous referees*for*their helpful comments and suggestions. ...##
###
Towards Effective Deep Learning for Constraint Satisfaction Problems
[chapter]

2018
*
Lecture Notes in Computer Science
*

Many attempts have been made to apply machine learning techniques to

doi:10.1007/978-3-319-98334-9_38
fatcat:djqet76n4bf6jdqebtioh5ik4m
*constraint**satisfaction**problems*(CSPs). However, none of them have made use of*the*recent advances in deep learning. ... To*the*best of our knowledge, this is*the*first effective application of deep learning to CSPs that yields >99.99% prediction accuracy on random Boolean*binary*CSPs whose*constraint*tightnesses or*constraint*...*The*research at*the*University of Southern California (USC) was supported by National Science Foundation (NSF) under grant numbers 1724392, 1409987, and 1319966. ...##
###
Stochastic Constraint Programming
[article]

2009
*
arXiv
*
pre-print

They combine together

arXiv:0903.1152v1
fatcat:lyq6id4uefb6lojov435u3jcnm
*the*best features of traditional*constraint**satisfaction*, stochastic integer programming, and stochastic*satisfiability*. ... To model combinatorial decision*problems*involving uncertainty and probability, we introduce stochastic*constraint*programming. ... If*the*fraction of*the*resulting*constraint**satisfaction**problems*that are*satisfiable*is at least equal to*the**threshold*θ, then*the*original stochastic*constraint**satisfaction**problem*is likely to be ...##
###
Constraint satisfaction problems and neural networks: A statistical physics perspective

2009
*
Journal of Physiology - Paris
*

On

doi:10.1016/j.jphysparis.2009.05.013
pmid:19616623
fatcat:ajpvvpa3ujg5tgay6jpvrmh5z4
*the*other hand some crucial inference*problems*in neurobiology, like those*generated*in multi-electrode recordings, naturally translate into hard*constraint**satisfaction**problems*. ... In particular,*the*use of cutting edge statistical physics concepts and methods allow one to solve very large*constraint**satisfaction**problems*like random*satisfiability*, coloring, or error correction. ... Conclusion*The*message passing strategy often provides*the*most efficient algorithms*for*solving hard*constraint**satisfaction**problems*, or*for*inference in graphical models. ...##
###
Constraint satisfaction problems and neural networks: a statistical physics perspective
[article]

2008
*
arXiv
*
pre-print

On

arXiv:0803.3061v1
fatcat:wadx7u6k6ralpgiypkimq4a2fu
*the*other hand some crucial inference*problems*in neurobiology, like those*generated*in multi-electrode recordings, naturally translate into hard*constraint**satisfaction**problems*. ... In particular,*the*use of cutting edge statistical physics concepts and methods allow one to solve very large*constraint**satisfaction**problems*like random*satisfiability*, coloring, or error correction. ... Conclusion*The*message passing strategy often provides*the*most efficient algorithms*for*solving hard*constraint**satisfaction**problems*, or*for*inference in graphical models. ...##
###
Lossy Data Compression with Random Gates

2005
*
Physical Review Letters
*

algorithm

doi:10.1103/physrevlett.95.038701
pmid:16090781
fatcat:expaem5gcjclzc6krbgt3yehiq
*for**constraint**satisfaction**problems*derived from statistical physics. ... We introduce a new protocol*for*a lossy data compression algorithm which is based on*constraint**satisfaction*gates. ... algorithm*for**constraint**satisfaction**problems*derived from statistical physics. ...##
###
Towards the Patterns of Hard CSPs with Association Rule Mining
[article]

2009
*
arXiv
*
pre-print

*The*hardness of finite domain

*Constraint*

*Satisfaction*

*Problems*(CSPs) is a very important research area in

*Constraint*Programming (CP) community. ... patterns of

*the*hardness of

*the*

*randomly*

*generated*CSPs ...

*Constraint*

*Satisfaction*

*Problems*A

*binary*

*Constraint*

*Satisfaction*

*Problem*(BCSP) is a CSP that

*satisfies*

*the*above (i) and (ii);

*the*only difference is

*the*

*constraint*set C. ...

##
###
Sharp Thresholds for a Random Constraint Satisfaction Problem

2017
*
Open Journal of Applied Sciences
*

*The*phenomenon of phase transition in

*constraint*

*satisfaction*

*problems*(CSPs) plays a crucial role in

*the*field of artificial intelligence and computational complexity theory. ...

*The*

*randomly*selected

*constraints*constitute a random CSP instance. An assignment that

*satisfies*all

*the*

*constraints*simultaneously is called a solution of

*the*CSP instance. ... Many

*problems*in

*the*fields of artificial intelligence, computer science and automatic control can be modeled as

*constraint*

*satisfaction*

*problems*. ...

##
###
A heuristic incremental modeling approach to course timetabling
[chapter]

1998
*
Lecture Notes in Computer Science
*

Speci cally, w e consider how a timetabling

doi:10.1007/3-540-64575-6_37
fatcat:625wqwoq2bd3tg7lecd4s2kkiu
*problem*can be represented as a*Constraint**Satisfaction**Problem*(CSP), and propose an algorithm*for*its solution which i m p r o ves upon*the*basic idea of backtracking ... In this paper*the*application of*constraint*-based reasoning to timetable*generation*is examined. ...*Satisfying*all of*the**constraints*does not guarantee 100% students*satisfaction*. ...##
###
A self-adaptive differential evolution algorithm for binary CSPs

2011
*
Computers and Mathematics with Applications
*

Attention is concentrated on varying F and CR dynamically with each

doi:10.1016/j.camwa.2011.06.053
fatcat:5k4k2xfywrckxcknn4bapm4jfi
*generation*evolution. SADE maintains*the*diversity of population and improves*the*global convergence ability. ... In order to balance an individual's exploration and exploitation capability*for*different evolving phases, F and CR are equal to two different self-adjusted nonlinear functions. ... We start with*the*necessary background on*Constraint**Satisfaction**Problems*and DE algorithms. In Section 3, we proposed SADE*for**binary*CSPs. ...##
###
On the Behavior and Application of Constraint Weighting
[chapter]

1999
*
Lecture Notes in Computer Science
*

We extend previous results from

doi:10.1007/978-3-540-48085-3_32
fatcat:sedmnx3thvgirpbwa2lnp7anoy
*satisfiability*testing by looking at*the*broader domain of*constraint**satisfaction*and test*for*differences in performance using*randomly**generated**problems*and*problems*... We find*constraint*weighting produces fairly consistent behaviour within*problem*domains, and is more influenced by*the*number and interconnectedness of*constraints*than*the*realism or randomness of a ... In addition we run tests on*the*well-studied*problem*of random*binary**constraint**satisfaction*[10] .*For**the*purpose of*the*research, a university timetable*problem**generator*was developed. ...
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