Proceedings of the workshop on Computational learning theory and natural learning systems (vol. 2) : intersections between theory and experiment: intersections between theory and experiment
A Glimpse of Constraint Satisfaction
Artificial Intelligence Review
Contradicting Conventional Wisdom in Constraint Satisfaction
PPCP '94 Proceedings of the Second International Workshop on Principles and Practice of Constraint Programming
CSPLIB: A Benchmark Library for Constraints
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
iOpt: A Software Toolkit for Heuristic Search Methods
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
EasyLocal++: an object-oriented framework for the flexible design of local-search algorithms
Software—Practice & Experience
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Efficient constraint propagation engines
ACM Transactions on Programming Languages and Systems (TOPLAS)
Compiling finite linear CSP into SAT
Constraints
Building structure into local search for SAT
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Constraint-Based Local Search
Limited discrepancy search revisited
Journal of Experimental Algorithmics (JEA)
Kangaroo: an efficient constraint-based local search system using lazy propagation
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
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Constraint programming is a powerful paradigm for solving constraint satisfaction problems, using various techniques. Amongst them, local search is a prominent methodology, particularly for large instances. However, it lacks uniformity, as it includes many variations accompanied by complex data structures, that cannot be easily brought under the same "umbrella." In this work we embrace their wide diversity by adopting propagation algorithms. Our constraint based local search (CBLS) system provides declarative alternative tools to express search methods, by exploiting conflict-sets of constraints and variables. Their maintenance is straightforward as it does not employ queues, unlike the state of the art CBLS systems. Thus, the propagation complexity is kept linear in the number of changes required after each assignment. Experimental results illustrate the capabilities, not only of the already implemented methods, such as hill climbing, simulated annealing, etc., but also the robustness of the underlying propagation engine.