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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/6359

Title: A logic for specifying agent actions and observations with probability
Authors: Rens, G
Lakemeyer, G
Meyer, T
Keywords: Partially observable Markov decision process
POMDP
Stochastic actions and observations
Domain specification
Tableau method
Issue Date: Aug-2012
Publisher: IOS Press
Citation: Rens, G, Lakemeyer, G and Meyer, T. A logic for specifying agent actions and observations with probability. STAIRS 2012 - Proceedings of the Sixth Starting AI Researchers' Symposium, Montpellier, France 27-28 August 2012
Series/Report no.: Workflow;9898
Abstract: We propose a non-standard modal logic for specifying agent domains where the agent’s actuators and sensors are noisy, causing uncertainty in action and perception. The logic is multi-modal, indexed with actions; the logic is also augmented with observation objects to facilitate knowledge engineers dealing with explicit observations in the environment, and it includes a notion of probability. A tableau method is provided for proving decidability of the proposed logic. It is our conjecture that the tableau rules are complete with respect to the semantics. The proof does not yet exist, however, we discuss the current approach of the proof and provide some examples to motivate our conjecture.
Description: STAIRS 2012 - Proceedings of the Sixth Starting AI Researchers' Symposium, Montpellier, France 27-28 August 2012. Published as an Open Access e-book.
URI: https://www.haiti.cs.uni-potsdam.de/proceedings/ECAI2012/content/stairs/stairs201223.pdf
http://www.booksonline.iospress.nl/Content/View.aspx?piid=31532
http://hdl.handle.net/10204/6359
Appears in Collections:Digital intelligence
General science, engineering & technology

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