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...
Many decision problems can be modelled as adversarial constraint satisfaction, which allows us to integrate methods from AI game playing. In particular, by using the idea of oppone...
The paper focuses on evaluating constraint satisfaction search algorithms on application based random problem instances. The application we use is a well-studied problem in the el...
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...
"Constraint satisfaction is a general problem in which the goal is to find values for a set of variables that will satisfy a given set of constraints. It is the core of many a...