Contingency selection in plan generation

Abstract

A key question in conditional planning is: how many, and which of the possible execution failures should be planned for? One cannot, in general, plan for all the failures that can be anticipated: there are simply too many. But neither can one ignore all the possible failures, or one will fail to produce sufficiently flexible plans. We describe a planning system that attempts to identify the contingencies that contribute the most to a plan's overall value. Plan generation proceeds by extending the plan to include actions that will be taken in case the identified contingencies fail, iterating until either a given expected value threshold is reached or the planning time is exhausted. We provide details of the algorithm, discuss its implementation in the Mahinur system, and give initial results of experiments comparing it with the C-Buridan approach to conditional planning.