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PDDL+ Planning via Constraint Answer Set Programming (1609.00030v1)

Published 31 Aug 2016 in cs.AI

Abstract: PDDL+ is an extension of PDDL that enables modelling planning domains with mixed discrete-continuous dynamics. In this paper we present a new approach to PDDL+ planning based on Constraint Answer Set Programming (CASP), i.e. ASP rules plus numerical constraints. To the best of our knowledge, ours is the first attempt to link PDDL+ planning and logic programming. We provide an encoding of PDDL+ models into CASP problems. The encoding can handle non-linear hybrid domains, and represents a solid basis for applying logic programming to PDDL+ planning. As a case study, we consider the EZCSP CASP solver and obtain promising results on a set of PDDL+ benchmark problems.

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Authors (3)
  1. Marcello Balduccini (17 papers)
  2. Daniele Magazzeni (42 papers)
  3. Marco Maratea (23 papers)
Citations (8)

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