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 modeling 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.
CITATION STYLE
Cashmore, M., Fox, M., Long, D., & Magazzeni, D. (2016). A compilation of the full PDDL+ language into SMT. In AAAI Workshop - Technical Report (Vol. WS-16-01-WS-16-15, pp. 583–591). AI Access Foundation. https://doi.org/10.1609/icaps.v26i1.13755
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