An agent based approach to the selection dilemma in CBR

Abstract

It is our understanding that a selection algorithm in Case Based Reasoning (CBR) must not only apply the principles of evolution found in nature, to the predicament of finding an optimal solution, but to be assisted by a methodology for problem solving based on the concept of agent. On the other hand, a drawback of any evolutionary algorithm is that a solution is better only in comparison to other(s), presently known solutions; such an algorithm actually has no concept of an optimal solution, or any way to test whether a solution is optimal. In this paper it is addressed the problem of The Selection Dilemma in CBR, where the candidate solutions are seen as evolutionary logic programs or theories, here understood as making the core of computational entities or agents, being the test whether a solution is optimal based on a measure of the quality-of-information that stems out of them.