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.
|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.|
|Number of pages||9|
|Publication status||Published - 30 Mar 2016|
- nonlinear continuous change
- planning algorithms
- artifical intelligence