Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Autocorrelation coefficient for the graph bipartitioning problem
Theoretical Computer Science
Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology
An Analysis of the Configuration Space of the Maximal Constraint Satisfaction Problem
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
The Density of States - A Measure of the Difficulty of Optimisation Problems
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Backbone fragility and the local search cost peak
Journal of Artificial Intelligence Research
When gravity fails: local search topology
Journal of Artificial Intelligence Research
Evidence for invariants in local search
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Simulated annealing applied to test generation: landscape characterization and stopping criteria
Empirical Software Engineering
Computing the density of states of Boolean formulas
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
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This paper presents an analysis of the search space of the well known NP-complete SAT problem. The analysis is based on a measure called "density of states" (d.o.s). We show experimentally that the distribution of assignments can be approximated by a normal law. This distribution allows us to get some insights about the behavior of local search algorithms.