Planning under Uncertainty in Dynamic Domains - Carnegie Mellon ...

Chapter 1IntroductionPlanning and problem solving are essential characteristics of intelligent behaviour andhave held a central place in AI research since the beginning of the eld. The emphasisof research in planning has most often been the design of ecient algorithms to ndplans given a simplied representation of a planning task, encoding only its essentialfeatures. By assuming a certain syntactic representation for planning domains andproblems, general-purpose planning algorithms could be designed and in some casesproofs could be given of their correctness and completeness [Fikes & Nilsson 1971;Tate 1977; Chapman 1987; Minton et al. 1989; McAllester & Rosenblitt 1991].While these systems represent signicant technical achievements, when we wantto apply them to problems that occur in the world around us we nd that the assumptionsthey make can be severely limiting. For example, their representations donot address trade-os between goals with dierent value in cases where they cannotall be achieved, or the possibility that the world can be changed independently of theactions taken by the planning agent. Nor do they address the fact that planners oftendo not know the state of the world or the eects of actions taken in it with certainty.Uncertainty aects a wide spectrum of planning domains, from Saturn orbit insertionfor the Cassini satellite (where the primary rocket may fail requiring thesecondary rocket to be primed before the maneuver) to a plan to have a picnic in apark (where one should take into account the chance of rain or that the park may becrowded). Frequently there are many things that can go wrong with each step of aplan and a detailed plan created in advance will almost certainly fail. For example,it is not feasible to create a detailed plan for driving to the oce that species turns,pauses and levels of acceleration before getting in the car. The planner does not knowif the trac lights will be red or green, or what trac will be encountered. This ledsome researchers to abandon programs that choose steps in advance in favour of \reactive"programs that choose each step as it is to be made [Agre & Chapman 1987;Schoppers 1989b].However it is often necessary to make contingency plans ahead of time even if notevery situation can be predicted and planned for. For example, the Cassini spacecraft'ssecondary rockets take several hours to re up, but must be ready immediately1