Evolutionary Adaptation in Case−Based Reasoning: An Application to Inter−Domain Analogies for Mediation

Abstract

Analogy plays a fundamental role in problem solving and it lies behind many processes central to human cognitive capacity, to the point that it has been considered "the core of cognition". Analogical reasoning functions through the process of transfer, the use of knowledge learned in one situation in another for which it was not targeted. The case-based reasoning (CBR) paradigm presents a highly related, but slightly different model of reasoning mainly used in artificial intelligence, different in part because analogical reasoning commonly focuses on cross-domain structural similarity whereas CBR is concerned with transfer of solutions between semantically similar cases within one specific domain. In this dissertation, we join these interrelated approaches from cognitive science, psychology, and artificial intelligence, in a CBR system where case retrieval and adaptation are accomplished by the Structure Mapping Engine (SME) and are supported by commonsense reasoning integrating information from several knowledge bases. For enabling this, we use a case representation structure that is based on semantic networks. This gives us a CBR model capable of recalling and adapting solutions from seemingly different, but structurally very similar domains, forming one of our contributions in this study. A traditional weakness of research on CBR systems has always been about adaptation, where most applications settle for a very simple "reuse" of the solution from the retrieved case, mostly through null adaptation or substitutional adaptation. The difficulty of adaptation is even more obvious for our case of cross-domain CBR using semantic networks. Solving this difficulty paves the way to another contribution of this dissertation, where we introduce a novel generative adaptation technique based on evolutionary computation that enables the spontaneous creation or modification of semantic networks according to the needs of CBR adaptation. For the evaluation of this work, we apply our CBR system to the problem of mediation, an important method in conflict resolution. The mediation problem is non-trivial and presents a very good real world example where we can spot structurally similar problems from domains seemingly as far as international relations, family disputes, and intellectual rights.