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» Solving quantified constraint satisfaction problems
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GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
15 years 11 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 10 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 10 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 10 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
15 years 5 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