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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.
|Title of host publication
|Subtitle of host publication
|20th European Conference on Artificial Intelligence, 27–31 August 2012, Montpellier, France – Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track
|Luc De Raedt, Christian Bessiere, Didier Dubois, Patrick Doherty, Paolo Frasconi, Fredrik Heintz, Peter Lucas
|252 - 257
|Published - 2012
|Frontiers in Artificial Intelligence and Applications
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- 1 Finished
1/11/2011 → 30/04/2013