Taming Discretised PDDL+ through Multiple Discretisations
Keywords: PDDL+, Hybrid Planning, Discretisation, Translation
TL;DR: Tackling PDDL+ problems is challenging and discretization is a common way to solve it. This paper proposes a reformulation approach allowing flexible encapsulation of multiple and dynamic discretization steps directly in PDDL+ models.
Abstract: The PDDL+ formalism allows the use of planning techniques in applications that require the ability to perform hybrid discrete-continuous reasoning. PDDL+ problems are notoriously challenging to tackle, and to reason upon them a well-established approach is discretisation. Existing systems rely on a single discretisation delta or, at most, two: a simulation delta to model the dynamics of the environment, and a planning delta, that is used to specify when decisions can be taken. However, there exist cases where this rigid schema is not ideal, for instance when agents with very different speeds need to cooperate or interact in a shared environment, and a more flexible approach that can accommodate more deltas is necessary. To address the needs of this class of hybrid planning problems, in this paper we introduce a reformulation approach that allows the encapsulation of different levels of discretisation in PDDL+ models, hence allowing any domain-independent planning engine to reap the benefits. Further, we provide the community with a new set of benchmarks that highlights the limits of fixed discretisation.
Primary Keywords: Knowledge Representation/Engineering
Category: Long
Student: Graduate
Submission Number: 156
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