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ICDCS
2000
IEEE
13 years 9 months ago
The Effect of Nogood Learning in Distributed Constraint Satisfaction
We present resolvent-based learning as a new nogood learning method for a distributed constraint satisfaction algorithm. This method is based on a look-back technique in constrain...
Makoto Yokoo, Katsutoshi Hirayama
FLAIRS
2004
13 years 6 months ago
Dynamic Agent-Ordering and Nogood-Repairing in Distributed Constraint Satisfaction Problems
The distributed constraint satisfaction problem (CSP) is a general formalization used to represent problems in distributed multi-agent systems. To deal with realistic problems, mu...
Lingzhong Zhou, John Thornton, Abdul Sattar
INFORMATICALT
2006
88views more  INFORMATICALT 2006»
13 years 4 months ago
Improving the Performances of Asynchronous Algorithms by Combining the Nogood Processors with the Nogood Learning Techniques
Abstract. The asynchronous techniques that exist within the programming with distributed constraints are characterized by the occurrence of the nogood values during the search for ...
Ionel Muscalagiu, Vladimir Cretu
CSCLP
2006
Springer
13 years 8 months ago
Extracting Microstructure in Binary Constraint Networks
Abstract. We present algorithms that perform the extraction of partial assignments from binary Constraint Satisfaction Problems without introducing new constraints. They are based ...
Chavalit Likitvivatanavong, Roland H. C. Yap
FLAIRS
2007
13 years 6 months ago
Search Ordering Heuristics for Restarts-Based Constraint Solving
Constraint Satisfaction Problems are ubiquitous in Artificial Intelligence. Over the past decade significant advances have been made in terms of the size of problem instance tha...
Margarita Razgon, Barry O'Sullivan, Gregory M. Pro...