Summarizing CSP hardness with continuous probability distributions

Authors:
Daniel Frost;Irina Rish;Lluís Vila
Affiliations:
Dept. of Information and Computer Science, University of California, Irvine, CA;Dept. of Information and Computer Science, University of California, Irvine, CA;Dept. of Information and Computer Science, University of California, Irvine, CA
Venue:
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Year:
1997

Citing 8
Cited 15

Goodness-of-fit techniques

Goodness-of-fit techniques
In search of the best constraint satisfaction search

AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
The hardest constraint problems: a double phase transition

Artificial Intelligence
Easy problems are sometimes hard

Artificial Intelligence
A Sufficient Condition for Backtrack-Free Search

Journal of the ACM (JACM)
Backtrack programming techniques

Communications of the ACM
A machine program for theorem-proving

Communications of the ACM
Validity of Normality Assumption in CSP Research

PRICAI '96 Proceedings of the 4th Pacific Rim International Conference on Artificial Intelligence: Topics in Artificial Intelligence

Random Constraint Satisfaction: Flaws and Structure

Constraints
Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems

Journal of Automated Reasoning
Resolution versus Search: Two Strategies for SAT

Journal of Automated Reasoning
Local Search Algorithms for SAT: An Empirical Evaluation

Journal of Automated Reasoning
Phase Transitions in Relational Learning

Machine Learning
Dynamic restart policies

Eighteenth national conference on Artificial intelligence
On the Fine Structure of Large Search Spaces

ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Search Strategies for Hybrid Search Spaces

ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Artificial intelligence and operations research: challenges and opportunities in planning and scheduling

The Knowledge Engineering Review
Statistical Regimes Across Constrainedness Regions

Constraints
Restart Strategy Selection Using Machine Learning Techniques

SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Lattice-search runtime distributions may be heavy-tailed

ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Evaluating las vegas algorithms: pitfalls and remedies

UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Impact of censored sampling on the performance of restart strategies

CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Statistical methodology for comparison of SAT solvers

SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing

Quantified Score

Hi-index	0.00

Visualization

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.