Efficient algorithms for combinatorial problems on graphs with bounded, decomposability—a survey
BIT - Ellis Horwood series in artificial intelligence
Tree search and ARC consistency in constraint satisfaction algorithms
Search in Artificial Intelligence
Tree clustering for constraint networks (research note)
Artificial Intelligence
Local and global relational consistency
Theoretical Computer Science - Special issue: principles and practice of constraint programming
Maintaining reversible DAC for Max-CSP
Artificial Intelligence
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
Bucket elimination: a unifying framework for reasoning
Artificial Intelligence
A general scheme for automatic generation of search heuristics from specification dependencies
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Arc Consistency for Soft Constraints
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
New Search Heuristics for Max-CSP
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Constraint Propagation for Soft Constraints: Generalization and Termination Conditions
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
A Comparison of Structural CSP Decomposition Methods
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Russian doll search for solving constraint optimization problems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
A scheme for approximating probabilistic inference
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
A sufficiently fast algorithm for finding close to optimal junction trees
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Tree approximation for belief updating
Eighteenth national conference on Artificial intelligence
Solving weighted CSP by maintaining arc consistency
Artificial Intelligence
Unifying tree decompositions for reasoning in graphical models
Artificial Intelligence
Computing lower bound for MAX-CSP problems
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
Semiring induced valuation algebras: Exact and approximate local computation algorithms
Artificial Intelligence
Multi-Objective Propagation in Constraint Programming
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Dynamic Orderings for AND/OR Branch-and-Bound Search in Graphical Models
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
AND/OR Branch-and-Bound search for combinatorial optimization in graphical models
Artificial Intelligence
Unifying tree decompositions for reasoning in graphical models
Artificial Intelligence
Improving DPOP with function filtering
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Join-graph propagation algorithms
Journal of Artificial Intelligence Research
Cluster Tree Elimination for Distributed Constraint Optimization with Quality Guarantees
Fundamenta Informaticae - RCRA 2008 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Bounded approximate decentralised coordination via the max-sum algorithm
Artificial Intelligence
Systematic vs. non-systematic algorithms for solving the MPE task
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
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Computing lower bounds to the best-cost extension of a tuple is an ubiquous task in constraint optimization. A particular case of special interest is the computation of lower bounds to all singleton tuples, since it permits domain pruning in Branch and Bound algorithms. In this paper we introduce MCTE(z), a general algorithm which allows the computation of lower bounds to arbitrary sets of tasks. Its time and accuracy grows as a function of z allowing a controlled tradeoff between lower bound accuracy and time and space to fit available resources. Subsequently, a specialization of MCTE(z) called MBTE(z) is tailored to computing lower bounds to singleton tuples. Preliminary experiments on Max-CSP show that using MBTE(z) to guide dynamic variable and value orderings in branch and bound yields a dramatic reduction in the search space and, for some classes of problems, this reduction is highly cost-effective producing significant time savings and is competitive against specialized algorithms for Max-CSP.