Heuristic planning for PDDL+ domains

TY - CHAP

T1 - Heuristic planning for PDDL+ domains

AU - Piotrowski, Wiktor

AU - Fox, Maria

AU - Long, Derek

AU - Magazzeni, Daniele

AU - Mercorio, Fabio

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85006136305&partnerID=8YFLogxK

M3 - Conference paper

AN - SCOPUS:85006136305

VL - 2016-January

SP - 3213

EP - 3219

BT - IJCAI International Joint Conference on Artificial Intelligence

PB - International Joint Conferences on Artificial Intelligence

T2 - 25th International Joint Conference on Artificial Intelligence, IJCAI 2016

Y2 - 9 July 2016 through 15 July 2016

ER -