Decision-Theoretic Planning with Fuzzy Notions in GOLOG

  • In this paper we present an extension of the action language Golog that allows for using fuzzy notions in non-deterministic argument choices and the reward function in decision-theoretic planning. Often, in decision-theoretic planning, it is cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, even for domain experts, it is not always easy to specify a reward function. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in Golog, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy uents. In Golog’s forward-search DT planning algorithm, these formulas are evaluated in order to find the agent’s optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order.

Export metadata

Additional Services

Share in X Search Google Scholar
Metadaten
Author:Stefan SchifferORCiD, Alexander FerreinORCiD
DOI:https://doi.org/10.1142/S0218488516400134
ISSN:1793-6411
Parent Title (English):International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Publisher:World Scientific
Place of publication:Singapur
Document Type:Article
Language:English
Year of Completion:2016
Volume:24
Issue:Issue Suppl. 2
First Page:123
Last Page:143
Link:https://doi.org/10.1142/S0218488516400134
Zugriffsart:bezahl
Institutes:FH Aachen / Fachbereich Elektrotechnik und Informationstechnik
FH Aachen / MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik
collections:Verlag / World Scientific