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authors Goel, Ashok Kumar
year 1989
title Integration of case-based reasoning and model-based reasoning for adaptive design problem solving
source Ohio State University
summary In the case-based approach to design, a novel problem is solved by adapting a design known to solve a related problem. Adapting a known design to solve a related problem by the commonly used methods of heuristic association and search, however, can be computationally expensive if the adaptation search space is not small. The adaptation space, then, needs to be decomposed into smaller and simpler spaces that can be searched more efficiently and effectively. The knowledge for decomposing the adaptation search space can be represented as a behavior-structure model that specifies how the structure of the known design results in its output behaviors. This research investigates the use of such behavior-structure models for adapting the designs of physical devices. Comprehension of how the output behaviors of a design arise from its structure is represented as a behavioral component-substance model for the design. The model explicitly specifies (i) the expected output behaviors of the design including its functions, (ii) the elementary structural and behavioral interactions between components and substances constituting the structure of the design, and (iii) the internal causal behaviors of the design that compose the elementary interactions into its output behaviors. The causal behaviors of the design, in this model, are indexed by the expected output behaviors for which they are responsible. The model aids case-based design in several ways. First, it identifies conceptual primitives for specifying the functions of designs, which are used to index the known designs stored in a case-based memory. Second, it identifies elementary types of behavior transformations and elementary types of structure modifications. Third, it provides knowledge for decomposition of the adaptation search space into smaller spaces so that the search for the needed structure modifications is localized. Fourth, it leads to a novel method for simulating the behavioral effects of structure modifications. The output and causal behaviors of the modified design, in this method, are derived by revising the output and causal behaviors of the known design. This integrative approach unifies case-based methods, associative methods, heuristic search methods, decomposition methods, and model-based methods into one architecture for adaptive design problem solving. Core portions of this approach have been implemented in an experimental design system called KRITIK.  
keywords Case Based Reasoning; Model Based Reasoning; Adaptive Design; Problem Solving
series thesis:PhD
references Content-type: text/plain
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