Opportunistic Branched Plans to Maximise Utility in the Presence of Resource Uncertainty

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

11 Citations (Scopus)
127 Downloads (Pure)

Abstract

In many applications, especially autonomous exploration, there is a trade-off between operational safety, forcing conservatism about resource usage; and maximising utility, requiring high resource utilisation. In this paper we consider a method of generating plans that maintain this conservatism whilst allowing exploitation of situations where resource usage is better than pessimistically estimated. We consider planning problems with soft goals, each with a violation cost. The challenge is to maximise utility (minimise the violation cost paid) whilst maintaining confidence that the plan will execute within the specified limits. We first show how forward search planning can be extended to generate such plans. Then we extend this to build branched plans: tree structures labelled with conditions on executing branches. Lower cost branches can be followed if their conditions are met. We demonstrate that the use of such plans can dramatically increase utility whilst still obeying strict safety constraints.
Original languageEnglish
Title of host publicationECAI 2012
Subtitle of host publication20th European Conference on Artificial Intelligence, 27–31 August 2012, Montpellier, France – Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track
EditorsLuc De Raedt, Christian Bessiere, Didier Dubois, Patrick Doherty, Paolo Frasconi, Fredrik Heintz, Peter Lucas
Pages252 - 257
ISBN (Electronic)9781614990987
DOIs
Publication statusPublished - 2012

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Volume242
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

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