A computational framework for package planning

Abstract

We consider a novel class of applications where a set of activities conducted by a group of people over a time period needs to be planned, taking into account each member's preference. We refer to the decision process that leads to such a plan as package planning. The problem differs from a number of well-studied AI problems including standard AI planning and decision-theoretic planning. We present a computational framework using a combination of activity grammar, heuristic search, decision theoretic graphical models, and dynamic preference aggregation. We show that the computation is tractable when the problem parameters are reasonably bounded.