Abstracting Noisy Robot Programs

T. Hoffman, Vaishak Belle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Abstraction is a commonly used process to represent some low-level system by a more coarse specification with the goal to omit unnecessary details while preserving important aspects. While recent work on abstraction in the situation calculus has focused on non-probabilistic domains, we describe an approach to abstraction of probabilistic and dynamic systems. Based on a variant of the situation calculus with probabilistic belief, we define a notion of bisimulation that allows to abstract a detailed probabilistic basic action theory with noisy actuators and sensors by a possibly non-stochastic basic action theory. By doing so, we obtain abstract Golog programs that omit unnecessary details and which can be translated to detailed programs for execution. This simplifies the implementation of noisy robot programs, opens up the possibility of using non-stochastic reasoning methods (e.g., planning) on probabilistic problems, and provides domain descriptions that are more easily interpretable.
Original languageEnglish
Title of host publicationProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems
Place of PublicationRichland, SC
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems
Number of pages9
ISBN (Electronic)9781450394321
Publication statusPublished - 30 May 2023
EventThe 22nd International Conference on Autonomous Agents and Multiagent Systems, 2023 - London, United Kingdom
Duration: 29 May 20232 Jun 2023
Conference number: 22


ConferenceThe 22nd International Conference on Autonomous Agents and Multiagent Systems, 2023
Abbreviated titleAAMAS 2023
Country/TerritoryUnited Kingdom
Internet address


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