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» Solving quantified constraint satisfaction problems
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GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
15 years 3 months ago
Transition models as an incremental approach for problem solving in evolutionary algorithms
This paper proposes an incremental approach for building solutions using evolutionary computation. It presents a simple evolutionary model called a Transition model in which parti...
Anne Defaweux, Tom Lenaerts, Jano I. van Hemert, J...
AI
2001
Springer
15 years 2 months ago
Search Techniques for Non-linear Constraint Satisfaction Problems with Inequalities
In recent years, interval constraint-based solvers have shown their ability to efficiently solve challenging non-linear real constraint problems. However, most of the working syst...
Marius-Calin Silaghi, Djamila Sam-Haroud, Boi Falt...
ICDCS
2000
IEEE
15 years 2 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
PACT
1999
Springer
15 years 1 months ago
Parallel Implementation of Constraint Solving
Many problems from artificial intelligence can be described as constraint satisfaction problems over finite domains (CSP(FD)), that is, a solution is an assignment of a value to ...
Alvaro Ruiz-Andino, Lourdes Araujo, Fernando S&aac...
AI
2005
Springer
14 years 9 months ago
Asynchronous aggregation and consistency in distributed constraint satisfaction
Constraint Satisfaction Problems (CSP) have been very successful in problem-solving tasks ranging from resource allocation and scheduling to configuration and design. Increasingly...
Marius-Calin Silaghi, Boi Faltings