CASP Solutions for Planning in Hybrid Domains

TL;DR

This paper introduces a method to encode PDDL+ planning problems into CASP, extending the EZCSP solver to handle hybrid discrete-continuous dynamics, and demonstrates its effectiveness through experimental analysis.

Contribution

It presents the first encoding of PDDL+ problems into CASP and extends the EZCSP solver to efficiently solve these hybrid planning problems.

Findings

The approach is viable for linear and non-linear PDDL+ domains.

Experimental results show competitive performance with existing planners.

The extended EZCSP solver successfully handles hybrid discrete-continuous problems.

Abstract

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.