Spatial Mental Models in Cognitive Systems

Article type: Research Article

Authors: Chen, Su-Shing

Affiliations: University of North Carolina, Charlotte, NC 28223, USA

Abstract: This paper is concerned with a mathematical foundation of representation issues and reasoning schemes of spatial information and knowledge. Spatial mental models in cognitive systems using a hybrid symbolic AI and highly parallel (e.g., neural networks or connectionism) framework of deductive and inductive reasoning in spatial domains will be constructed. The framework for “induction” of Holland, Holyoak, Nisbett, and Thagard was proposed as the classifer system approach to inferential and learning processes in biological cognitive systems which remedies the inadequacies of the classical logical approaches to induction: formal inductive logics. In this paper, we use a hybrid symbolic and highly parallel approach instead of the classifier system only.

DOI: 10.3233/FI-1993-182-407

Journal: Fundamenta Informaticae, vol. 18, no. 2-4, pp. 183-192, 1993