The introduction of PDDL+ allowed more accurate representations of complex real-world problems of interest to the scientific community. However, PDDL+ problems are notoriously challenging to planners, requiring more advanced heuristics. We introduce the Temporal Pattern Database (TPDB), a new domain-independent heuristic technique designed for PDDL+ domains with mixed discrete/continuous behaviour, non-linear system dynamics, processes, and events. The pattern in the TPDB is obtained through an abstraction based on time and state discretisation. Our approach combines constraint relaxation and abstraction techniques, and uses solutions to the relaxed problem, as a guide to solving the concrete problem with a discretisation fine enough to satisfy the continuous model's constraints.

Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F. (2017). PDDL+ Planning with temporal pattern databases. In The AAAI-17 Workshop on Symbolic Inference and Optimization (pp.930-936). AI Access Foundation.

PDDL+ Planning with temporal pattern databases

MERCORIO, FABIO
2017

Abstract

The introduction of PDDL+ allowed more accurate representations of complex real-world problems of interest to the scientific community. However, PDDL+ problems are notoriously challenging to planners, requiring more advanced heuristics. We introduce the Temporal Pattern Database (TPDB), a new domain-independent heuristic technique designed for PDDL+ domains with mixed discrete/continuous behaviour, non-linear system dynamics, processes, and events. The pattern in the TPDB is obtained through an abstraction based on time and state discretisation. Our approach combines constraint relaxation and abstraction techniques, and uses solutions to the relaxed problem, as a guide to solving the concrete problem with a discretisation fine enough to satisfy the continuous model's constraints.
paper
Artificial Intelligence; Planning; Hybrid Systems
English
The AAAI-17 Workshop on Symbolic Inference and Optimization
2017
Piotrowski, W; Fox, M; Long,D; Magazzeni, D; Mercorio, F
The AAAI-17 Workshop on Symbolic Inference and Optimization
9781577357865
2017
WS-17-01
930
936
https://aaai.org/Library/Workshops/ws17-14.php
open
Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F. (2017). PDDL+ Planning with temporal pattern databases. In The AAAI-17 Workshop on Symbolic Inference and Optimization (pp.930-936). AI Access Foundation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/156158
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