Abstract

Since the release of PDDL 2.1, many planners accepted the challenge of addressing more complicated domains and problems, including both temporal and numeric features for scheduling and resources management. However, very few planners can handle a significant subset of the features that the language allows for modeling. To handle a level of expressiveness sufficient to work with more realistic problems, we have designed NextFLAP (Numeric EXpressions in TFLAP). The planner follows a hybrid approach, which combines a forward partial-order planner with a numeric constraint solver/optimizer. Additionally, we include a new feature, the control parameters, which are relevant for direct modeling numerical quantities and physical properties of objects in the actions, such as ‘partially charging of a battery’ or ‘obtaining a certain amount of resources’. This feature overcomes a limitation of the PDDL language, which is that the parameters of the actions must be objects (finite domain values) and, in no case, numeric variables. In this paper we illustrate the advantages of using these temporal and numeric modeling features and then describe our planning system, NextFLAP, that can handle these domains. We show that NextFLAP is competitive with other state-of-the-art planners and that it generates good-quality plans.

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