The paper addresses the problem of plan repair for tasks involving mandatory constraints on consumable and continuous resources, modeled as numeric fluents. The approach starts by proposing a new notion of numeric macro actions allowing to handle - as an extension to the classical macro action formulation - conditions and operations not only on the propositional fragment, but also on the numeric one. By reasoning directly on the current plan, the paper shows two techniques for selecting useful macro actions. Such macro actions, toghether with the original actions model, are then used by an off-the-shelf numeric planner for a faster plan repair task. To evaluate the techniques and the contribution of numeric macro actions, we experimented the approach on several numeric planning domains using Metric-FF as off-the-shelf planner.Results show that both strategies enhance the performance of the same planning system without macro actions. Even, one of the strategies turns out to be very competitive also with the specialized plan repair system LPG-ADAPT, both in terms of cpu-time, and stability of the repaired plan.

Plan Repair for Resource Constrained Tasks via Numeric Macro Actions

SCALA, ENRICO
2014-01-01

Abstract

The paper addresses the problem of plan repair for tasks involving mandatory constraints on consumable and continuous resources, modeled as numeric fluents. The approach starts by proposing a new notion of numeric macro actions allowing to handle - as an extension to the classical macro action formulation - conditions and operations not only on the propositional fragment, but also on the numeric one. By reasoning directly on the current plan, the paper shows two techniques for selecting useful macro actions. Such macro actions, toghether with the original actions model, are then used by an off-the-shelf numeric planner for a faster plan repair task. To evaluate the techniques and the contribution of numeric macro actions, we experimented the approach on several numeric planning domains using Metric-FF as off-the-shelf planner.Results show that both strategies enhance the performance of the same planning system without macro actions. Even, one of the strategies turns out to be very competitive also with the specialized plan repair system LPG-ADAPT, both in terms of cpu-time, and stability of the repaired plan.
2014
INTERNATIONAL CONFERENCE ON AUTOMATED PLANNING AND SCHEDULING
Portsmouth, New Hampshire, USA
June 21–26, 2014
PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL CONFERENCE ON AUTOMATED PLANNING AND SCHEDULING
Association for the Advancement of Artificial Intelligence
280
288
9781577356608
http://www.aaai.org/ocs/index.php/ICAPS/ICAPS14/paper/view/7900
Aomated Planning; Plan repair; Plan Execution
Enrico Scala
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/151053
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