AAAI Publications, Sixteenth International Conference on Principles of Knowledge Representation and Reasoning

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Complexity of Projection with Stochastic Actions in a Probabilistic Description Logic
Benjamin Zarrieß

Last modified: 2018-09-24

Abstract


We consider an action language extended with quantitative notions of uncertainty. In our setting, the initial beliefs of an agent are represented as a probabilistic knowledge base with axioms formulated in the Description Logic ALCO. Action descriptions describe the possibly context-sensitive and non-deterministic effects of actions and provide likelihood distributions over the different possible outcomes of actions. In this paper, we prove decidability of the projection problem which is the basic reasoning task needed for predicting the outcome of action sequences. Furthermore, we investigate how the non-determinism in the action model affects the complexity of the projection problem.

Keywords


Reasoning about Actions; Description Logic; Probabilistic Uncertainty

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