A Compilation of the Full PDDL+ Language into SMT
Cashmore, Michael (King's College London) | Fox, Maria (Kings College London) | Long, Derek (Kings College London) | Magazzeni, Daniele (Kings College London)
Planning in hybrid systems is important for dealing with real world 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.
Apr-12-2016
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