Planning with hybrid domains modelled in PDDL+ has been gaining research interest in the Automated Planning community in recent years. Hybrid domain models capture a more accurate representation of real world problems that involve continuous processes than is possible using discrete systems. However, solving problems represented as PDDL+ domains is very challenging due to the construction of complex system dynamics, including non-linear processes and events. In this paper we introduce DiNo, a new planner capable of tackling complex problems with non-linear system dynamics governing the continuous evolution of states. DiNo is based on the discretise-and-validate approach and uses the novel Staged Relaxed Planning Graph+ (SRPG+) heuristic, which is introduced in this paper. Although several planners have been developed to work with subsets of PDDL+ features, or restricted forms of processes, DiNo is currently the only heuristic planner capable of handling non-linear system dynamics combined with the full PDDL+ feature set.

Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F. (2016). Heuristic Planning for PDDL+ domains. In AAAI Workshop - Technical Report (pp.615-623). AI Access Foundation.

Heuristic Planning for PDDL+ domains

Mercorio F.
2016

Abstract

Planning with hybrid domains modelled in PDDL+ has been gaining research interest in the Automated Planning community in recent years. Hybrid domain models capture a more accurate representation of real world problems that involve continuous processes than is possible using discrete systems. However, solving problems represented as PDDL+ domains is very challenging due to the construction of complex system dynamics, including non-linear processes and events. In this paper we introduce DiNo, a new planner capable of tackling complex problems with non-linear system dynamics governing the continuous evolution of states. DiNo is based on the discretise-and-validate approach and uses the novel Staged Relaxed Planning Graph+ (SRPG+) heuristic, which is introduced in this paper. Although several planners have been developed to work with subsets of PDDL+ features, or restricted forms of processes, DiNo is currently the only heuristic planner capable of handling non-linear system dynamics combined with the full PDDL+ feature set.
paper
planning; artificial intelligence; hybrid system; PDDL
English
30th AAAI Conference on Artificial Intelligence, AAAI 2016 - 12 February 2016 through 13 February 2016
2016
AAAI Workshop - Technical Report
9781577357599
2016
WS-16-01 - WS-16-15
615
623
none
Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F. (2016). Heuristic Planning for PDDL+ domains. In AAAI Workshop - Technical Report (pp.615-623). AI Access Foundation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/466527
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