In many practical domains, planning systems are required to reason about durative actions. A common assumption in the literature is that the executor is allowed to decide the duration of each action. However, this assumption may be too restrictive for applications. In this paper, we tackle the problem of temporal planning with uncontrollable action durations. We show how to generate robust plans, that guarantee goal achievement despite the uncontrollability of the actual duration of the actions. We extend the state-space temporal planning framework, integrating recent techniques for solving temporal problems under uncertainty. We discuss different ways of lifting the total order plans generated by the heuristic search to partial order plans, showing (in)completeness results for each of them. We implemented our approach on top of COLIN, a state-of-the-art planner. An experimental evaluation over several benchmark problems shows the practical feasibility of the proposed approach.

Strong Temporal Planning with Uncontrollable Durations: a State-Space Approach

Cimatti, Alessandro;Micheli, Andrea;Roveri, Marco
2015

Abstract

In many practical domains, planning systems are required to reason about durative actions. A common assumption in the literature is that the executor is allowed to decide the duration of each action. However, this assumption may be too restrictive for applications. In this paper, we tackle the problem of temporal planning with uncontrollable action durations. We show how to generate robust plans, that guarantee goal achievement despite the uncontrollability of the actual duration of the actions. We extend the state-space temporal planning framework, integrating recent techniques for solving temporal problems under uncertainty. We discuss different ways of lifting the total order plans generated by the heuristic search to partial order plans, showing (in)completeness results for each of them. We implemented our approach on top of COLIN, a state-of-the-art planner. An experimental evaluation over several benchmark problems shows the practical feasibility of the proposed approach.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/264220
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