Argument diagramming tools can improve reasoning and learning. They are likely to have a significant place in future virtual learning environments whose design will be dominated b...
Abstract. Different mutation operators have been proposed in evolutionary programming. However, each operator may be efficient in solving a subset of problems, but will fail in an...
In this paper, we propose a family of operators for merging stratified knowledge bases under integrity constraints. The operators are defined in a model-theoretic way. Our merging...
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
The authors propose a co-adaptive approach to controlling parameters for coevolution-based learning classifier systems. By taking advantage of the on-line incremental learning capa...