A compilation of the full PDDL+ language into SMT

Michael  Cashmore; Maria  Fox; Derek  Long; Daniele  Magazzeni

A compilation of the full PDDL+ language into SMT

Michael Cashmore
, Maria Fox
, Derek Long
, Daniele Magazzeni

Computer And Information Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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Abstract

Planning in hybrid systems is important for dealing with realworld applications. PDDL+ supports this representation of domains with mixed discrete and continuous dynamics, and supports events and processes modelling exogenous change. Motivated by numerous SAT-based planning approaches, we propose an approach to PDDL+ planning through SMT, describing an SMT encoding that captures all the features of the PDDL+ problem as published by Fox and Long (2006). The encoding can be applied on domains with nonlinear continuous change. We apply this encoding in a simple planning algorithm, demonstrating excellent results on a set of benchmark problems.

Original language	English
Title of host publication	Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling (ICAPS 2016)
Place of Publication	Menlo Park, US-CA.
Pages	583-591
Number of pages	9
Volume	2016-January
Publication status	Published - 30 Mar 2016

Keywords

PDDL+
planning
nonlinear continuous change
planning algorithms
AI
artifical intelligence

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N2 - Planning in hybrid systems is important for dealing with realworld applications. PDDL+ supports this representation of domains with mixed discrete and continuous dynamics, and supports events and processes modelling exogenous change. Motivated by numerous SAT-based planning approaches, we propose an approach to PDDL+ planning through SMT, describing an SMT encoding that captures all the features of the PDDL+ problem as published by Fox and Long (2006). The encoding can be applied on domains with nonlinear continuous change. We apply this encoding in a simple planning algorithm, demonstrating excellent results on a set of benchmark problems.

AB - Planning in hybrid systems is important for dealing with realworld applications. PDDL+ supports this representation of domains with mixed discrete and continuous dynamics, and supports events and processes modelling exogenous change. Motivated by numerous SAT-based planning approaches, we propose an approach to PDDL+ planning through SMT, describing an SMT encoding that captures all the features of the PDDL+ problem as published by Fox and Long (2006). The encoding can be applied on domains with nonlinear continuous change. We apply this encoding in a simple planning algorithm, demonstrating excellent results on a set of benchmark problems.

KW - PDDL+

KW - planning

KW - nonlinear continuous change

KW - planning algorithms

KW - AI

KW - artifical intelligence

UR - https://www.aaai.org/ocs/index.php/ICAPS/ICAPS16/paper/view/13101

M3 - Conference contribution book

VL - 2016-January

SP - 583

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BT - Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling (ICAPS 2016)

CY - Menlo Park, US-CA.

ER -

A compilation of the full PDDL+ language into SMT

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Keywords

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