A Review of knowledge-based planning techniques

Abstract

SummaryPlanning systems have been an active research topic within Artificial Intelligence for over two decades. There have been a number of techniques developed during that period which still form an essential part of many of today's planners. This paper introduces the techniques, attempts to classify some of the important research themes in AI planning and describes their historical development.

On distinguishing epistemic from pragmatic action

“…As suggested earlier, existing literature on planning (Tate, Hendler, & Drummond, 1990), action theory (Bratman, 1987), and to a lesser extent decision theory (Chernoff & Moses, 1967) has focused almost exclusively on pragmatic actions. In such studies, actions are defined as transformations in physical or social space.…”

Qualitative Spatial Representation and Reasoning

“…Although robotic navigation ultimately requires numerically specified directions to the robot to move or turn, hierarchical planning with detailed decisions (e.g., how or exactly where to move) being delayed until a high level plan have been achieved has been shown to be effective [196]. Further, the robot's model of its environment may be imperfect, leading to an inability to use standard robot navigation techniques.…”

The effective field of view paradigm: adding representation to a reactive system

“…Typically, classical planners (see [29] for an overview) make the impractical assumptions of complete and omniscient sensing. Reactive systems [10] alleviate the problems with these assumptions by always computing the currently necessary information from the current set of sensor values.…”