Abstract
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.
| Original language | English |
|---|---|
| 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. |
| Pages | 583-591 |
| Number of pages | 9 |
| Volume | 2016-January |
| Publication status | Published - 30 Mar 2016 |
Keywords
- PDDL+
- planning
- nonlinear continuous change
- planning algorithms
- AI
- artifical intelligence
