Representing Uncertainty in Simple Planners, Principles of Knowledge Representation and Reasoning

    Abstract

    In this paper, we present an analysis of planning with uncertain information regarding both the state of the world and the effects of actions using a Strips- or (propositional) Adl-style representation. We provide formal definitions of plans under incomplete information and conditional plans, and describe Plinth, a conditional linear planner based on these definitions. We also clarify the definition of the term “conditional action, ” which has been variously used to denote actions with context-dependent effects and actions with uncertain outcomes. We show that the latter can, in theory, be viewed as a special case of the former but that to do so requires one to sacrifice the simple, single-model representation for one which can distinguish between a proposition and beliefs about that proposition.

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