Making compromises among antagonist constraints in a planner
Artificial Intelligence
Artificial intelligence (2nd ed.)
Artificial intelligence (2nd ed.)
OOPSLA '87 Conference proceedings on Object-oriented programming systems, languages and applications
Tree search and ARC consistency in constraint satisfaction algorithms
Search in Artificial Intelligence
Preferences; Putting More Knowledge into Queries
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Modeling Engineering Structures with Constrained Objects
PADL '02 Proceedings of the 4th International Symposium on Practical Aspects of Declarative Languages
Constraints for Object Recognition in Aerial Images - Handling of Unobserved Features
CP '98 Proceedings of the 4th International Conference on Principles and Practice of Constraint Programming
A Semantic web approach to handling soft constraints in virtual organisations
Electronic Commerce Research and Applications
IncrementParsing '04 Proceedings of the Workshop on Incremental Parsing: Bringing Engineering and Cognition Together
An Efficient Algorithm for Solving Dynamic Complex DCOP Problems
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Mixed constraint satisfaction: a framework for decision problems under incomplete knowledge
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
A constraint satisfaction framework for decision under uncertainty
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Possibilistic constraint satisfaction problems or "How to handle soft constraints ?"
UAI'92 Proceedings of the Eighth international conference on Uncertainty in artificial intelligence
Component qos contract negotiation in multiple containers
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part II
Assisting domain experts to formulate and solve constraint satisfaction problems
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
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A constraint satisfaction problem involves finding values for variables subject to constraints on which combinations of values are allowed. In some cases it may be impossible or impractical to solve these problems completely. We may seek to partially solve the problem in an "optimal" or "sufficient" sense. A formal model is presented for defining and studying such partial constraint satisfaction problems. The basic components of this model are a constraint satisfaction problem, a problem space, and a metric on that space. Algorithms for solving partial constraint satisfaction problems are discussed. A specific branch and bound algorithm is described. Some initial experimental experience with this algorithm is presented.