AIApr 12, 2017

CASP Solutions for Planning in Hybrid Domains

arXiv:1704.03574v23 citations
AI Analysis

This work addresses planning in hybrid domains for automated planning researchers, but it appears incremental as it adapts existing methods to a new data type.

The paper tackles the problem of solving PDDL+ planning domains, which involve mixed discrete-continuous dynamics, by encoding them into CASP and extending the EZCSP solver. The result shows viability through experimental analysis on linear and non-linear variants, though no concrete numbers are provided.

CASP is an extension of ASP that allows for numerical constraints to be added in the rules. PDDL+ is an extension of the PDDL standard language of automated planning for modeling mixed discrete-continuous dynamics. In this paper, we present CASP solutions for dealing with PDDL+ problems, i.e., encoding from PDDL+ to CASP, and extensions to the algorithm of the EZCSP CASP solver in order to solve CASP programs arising from PDDL+ domains. An experimental analysis, performed on well-known linear and non-linear variants of PDDL+ domains, involving various configurations of the EZCSP solver, other CASP solvers, and PDDL+ planners, shows the viability of our solution.

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