Research and Design of Planning Systems in the AORBCO Model

Abstract

Abstract Planning research in artificial intelligence began earlier, dating back to 1969, and the general problem solver (GPS) designed by Newell and Simon [1]. Since then, other researchers have also proposed other planners, such as QA3 system using theorem proving method to construct planning[2], Fikes and Nilsson designed STRIPS planning system [3], until today STRIPS planning method is still only a very important research method in the field of planning. After more than 50 years of research, there have been many intelligent planning methods such as graph planning method, probability planning, timing planning, heuristic planning and perceptual planning. Although the existing intelligent planning methods have been able to solve some problems, the existing planning mainly focuses on the design of the planning algorithm, and the manual analysis preprocessing workload is large. Research has pointed out that the new generation of intelligent planners should be knowledge-based development of knowledge-based planning systems is a meaningful work [4]. Therefore, by analyzing the existing intelligent planning methods and AORBCO model, this paper gives the definition of intelligent planning with self-consciousness, and proposes an intelligent planning method based on self-consciousness based on behavior control.