Browse Theses

This research addresses the problem of developing planning knowledge-based applications. In particular, it is concerned with the problems of knowledge acquisition and representation—the issues that remain an impediment to the development of large-scale, knowledge-based planning applications. This work aims to develop a model of planning problem solving that facilitates expert knowledge elicitation and also supports effective problem solving. Achieving this goal requires determining the types of knowledge used by planning experts, the structure of this knowledge, and the problem-solving process that results in the plan. While answering these questions it became clear that the knowledge structure, as well as the process of problem solving, largely depends on the knowledge available to the expert. This dissertation proposes classification of planning problems based on their use of expert knowledge. Such classification can help in the selection of the appropriate planning method when dealing with a specific planning problem.

The research concentrates on one of the identified classes of planning problems that can be characterized by well-defined and well-structured problem-solving knowledge. To achieve a more complete knowledge representation architecture for such problems, this work employs the task-specific approach to problem solving. The result of this endeavor is a task-specific methodology that allows the representation and use of planning knowledge in a structural, consistent manner specific to the domain of the application.

The shell for building a knowledge-based planning application was created as a proof of concept for the methodology described in this dissertation. This shell enabled the development of a system for manufacturing planning—COMPLAN. COMPLAN encompasses knowledge related to four generic techniques used in composite material manufacturing and, given the description of the composite part, creates a family of plans capable of producing it.