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...
We report (to our knowledge) the first evaluation of Constraint Satisfaction as a computational framework for solving closest string problems. We show that careful consideration o...
In this paper we report a new approach to generating predictions about skilled interactive cognition. The approach, which we call Cognitive Constraint Modeling, takes as input a d...
Alonso H. Vera, Andrew Howes, Michael McCurdy, Ric...
We report the first evaluation of Constraint Satisfaction as a computational framework for solving closest string problems. We show that careful consideration of symbol occurrenc...
The contribution of this paper is in demonstrating the impact of AND/OR search spaces view on solutions counting. In contrast to the traditional (OR) search space view, the AND/OR ...