How can knowledge-based systems solve large-scale problems?: model-based decomposition and problem solving

摘要

A knowledge-based system that can solve large-scale problems is discussed. It is provided with a new method which combines model building with hierarchical problem decomposition. The model-based approach to problem solving is a general method which is ordinarily used by humans. With this method, representations of the problem and the problem-solving process can be separated. Thus, computers provided with this method allows the end user to focus his/her attention on the description of the problem, without paying attention to the description of the method for solving this problem by computer. When a problem becomes large and complex, however, it becomes difficult to solve by this simple model-based method, and it must be combined with another technique to decompose the problem into a set of smaller ones, each of which is simple enough to deal with. This does not assume that the original problem can be decomposed into the same components, because, in general, a problem involves heterogeneous components.A prototype of a system which could implement this idea has been developed, and its effectiveness has partly been proved. Experimentation is going to be carried out on the total system. The paper discusses a method of implementing the idea with the example of representation.