Probabilistic Reasoning about Actions in Nonmonotonic Causal Theories
Artificial Intelligence
2012-12-12 v1
Abstract
We present the language {m P}{cal C}+ for probabilistic reasoning about actions, which is a generalization of the action language {cal C}+ that allows to deal with probabilistic as well as nondeterministic effects of actions. We define a formal semantics of {m P}{cal C}+ in terms of probabilistic transitions between sets of states. Using a concept of a history and its belief state, we then show how several important problems in reasoning about actions can be concisely formulated in our formalism.
Keywords
Cite
@article{arxiv.1212.2461,
title = {Probabilistic Reasoning about Actions in Nonmonotonic Causal Theories},
author = {Thomas Eiter and Thomas Lukasiewicz},
journal= {arXiv preprint arXiv:1212.2461},
year = {2012}
}
Comments
Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)