Knowledge structures for planning in realistic domains

Abstract

AbstractIn this paper we discuss techniques for representing and organizing knowledge that enable a planning system to work effectively in large and realistic task domains. We consider the following engineering issues: (i) generating and manipulating large and complex plans; (ii) managing large and complex knowledge bases; and (iii) operating with an incomplete knowledge base and/or world model.A theme reflected throughout the paper is the policy of developing common representations useful in many modules of the planning system. We believe these representations will be useful in other artificial intelligence systems with similar demands on knowledge and reasoning skills. We present uniform representations for (i) descriptions of objects and actions, including partial and indefinite descriptions, (ii) world knowledge of task domains, (iii) a trace of the planning process that includes alternative solutions, and (iv) an organizational mechanism for both the world knowledge as well as the knowledge gathered during the planning process (e.g. the constraints among the objects and actions contained in a plan solution)