Timelines are a formalism to model planning domains where the temporal aspects are predominant, and have been used in many real-world applications. Despite their practical success, a major limitation is the inability to model temporal uncertainty, i.e. the plan executor cannot decide the duration of some activities. In this paper we make two key contributions. First, we propose a comprehensive, semantically well founded framework that (conservatively) extends with temporal uncertainty the state of the art timeline approach. Second, we focus on the problem of producing time-triggered plans that are robust with respect to temporal uncertainty, under a bounded horizon. In this setting, we present the first complete algorithm, and we show how it can be made practical by leveraging the power of Satisfiability Modulo Theories.

Timelines with Temporal Uncertainty

Cimatti, Alessandro;Micheli, Andrea;
2013-01-01

Abstract

Timelines are a formalism to model planning domains where the temporal aspects are predominant, and have been used in many real-world applications. Despite their practical success, a major limitation is the inability to model temporal uncertainty, i.e. the plan executor cannot decide the duration of some activities. In this paper we make two key contributions. First, we propose a comprehensive, semantically well founded framework that (conservatively) extends with temporal uncertainty the state of the art timeline approach. Second, we focus on the problem of producing time-triggered plans that are robust with respect to temporal uncertainty, under a bounded horizon. In this setting, we present the first complete algorithm, and we show how it can be made practical by leveraging the power of Satisfiability Modulo Theories.
2013
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence
USA
AAAI Press
Cimatti, Alessandro; Micheli, Andrea; Marco, Roveri
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/33658
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