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 Proceeding of 25th International Joint Conference on Artificial Intelligence (pp.3213-3219). Palo Alto : International Joint Conferences on Artificial Intelligence.

Heuristic planning for PDDL+ domains

MERCORIO, FABIO
Ultimo
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
PDD, hybrid system, heuristic search
English
The 25th International Joint Conference on Artificial Intelligence (IJCAI)
2016
Piotrowski, W; Fox, M; Long, D; Magazzeni, D; Mercorio, F
Proceeding of 25th International Joint Conference on Artificial Intelligence
978-1-57735-770-4
2016
2016-
3213
3219
1271
http://www.ijcai.org/Proceedings/16/Papers/455.pdf
partially_open
Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F. (2016). Heuristic planning for PDDL+ domains. In Proceeding of 25th International Joint Conference on Artificial Intelligence (pp.3213-3219). Palo Alto : International Joint Conferences on Artificial Intelligence.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/116629
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