Titlebook: An Introduction to the Planning Domain Definition Language; Patrik Haslum,Nir Lipovetzky,Christian Muise Book 2019 Springer Nature Switzer

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Discrete and Deterministic Planning,PDDL supports the expression of several different classes of planning problems. In this chapter and the next, we begin with the simplest class of planning problems, which are discrete, finite, and deterministic. This kind of planning is often called . (to distinguish it from the many different extensions that have later followed).

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978-3-031-00456-8Springer Nature Switzerland AG 2019

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https://doi.org/10.1007/978-3-642-80728-2, the language has been extended in key ways which we discuss here in this chapter. The modifications empower the modeller to succinctly represent complex but common phenomenon in the planning setting, but do not necessarily change the theoretical expressiveness of the language. We discuss these det

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https://doi.org/10.1007/3-540-29862-2t is, they can only take values true and false. The numeric planning subset of PDDL introduces state variables whose values are (rational) numbers. These are instances of .. The range of a numeric function in PDDL is unbounded, which means there is an infinite set of values it can take. A state is s

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https://doi.org/10.1007/3-540-29862-2ay, through the introduction of . In temporal planning, actions are durative in nature, and both the conditions and effects of an action must be generalised accordingly. Temporal planning was introduced into PDDL with the 2002 IPC, although of course there were temporal planners long before that [e.

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Wie eine Arztpraxis werben kann,ut this text, we have seen a range of the more commonly used subsets of PDDL, as well as a variety of modelling examples demonstrating the expressiveness of each. The widespread use of PDDL stems from the collaborative efforts of the planning community, and the desire for a language to facilitate be

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