Locally Global Planning: Decision-Theoretic Planning in OSCAR

It is conjectured that MDP and POMDP planning will remain unfeasible for complex domains, so some form of ÒclassicalÓ decision-theoretic planning is sought. However, local plans cannot be properly compared in terms of their expected values, because those values will be affected by the other plans the agent has adopted. Plans must instead be merged into a single ÒmasterplanÓ, and new plans evaluated in terms of their contribution to the value of the master plan. To make both the construction and evaluation of plans feasible, it is proposed to evaluate plans and their interactions defeasibly. 1. Approaches to Decision-Theoretic Planning Two assumptions made by classical planning are: (1) the agent has full knowledge about the consequences of its actions in any circumstances; and (2) all that is important about a plan is that it achieves its goal. For an applied planning problem pertaining to a narrowly circumscribed domain, we might be able to pretend that the first assumption holds, but not for planning in an autonomous agent operating in a complex and only partially predictable environment. This problem can be handled in part by reasoning defeasibly about the consequences of actions, as I described in my (1998), but that is at best a partial solution. Turning to the second assumption, it is generally recognized that in evaluating plans we have to weigh the value of the goal achieved against the cost of achieving it. That cost can consist of both normal execution costs and the costs (positive and negative) of possible side effects. The costs of side effects can include things like opportunity costs. Executing one plan can make it impossible (or merely more difficult or more expensive) to execute another plan. Furthermore, nothing is certain. We have to discount the value of the goal by the probability of achieving it, and discount execution costs similarly by their probabilities. In other words, we must evaluate plans decisiontheoretically.