Memory Architecture for Argumentation-based Adaptive System

A. Ayesh (UK)


Knowledge Representation, Distributed AI, Neuro psychology, and memory architecture


Thinking, decision making and hence adapting are all influenced often by mentally recognizing objects or situations. As a result the associated features of the given object or situation are recalled. This could be a lengthy process if traditional computation retrieval processes are used. In humans, however, the process of memorizing is often based on emphasized associated features rather than all the features of the given object. This feature-selective memorization becomes of a tremendous importance in developing argumentative-based adaptation process that simulates the human thinking process. In this paper we represent a preliminary research on using the factor of selected features in enabling the anchoring of information to objects and concepts.

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