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Back [PhD thesis] Effective planning with expressive languages

[PhD thesis] Effective planning with expressive languages

Author: Guillem Francès

Supervisor: Héctor Geffner

Classical planning is concerned with finding sequences of actions that achieve a certain goal from an initial state of the world, assuming that actions are deterministic, states are fully known, and both are described in some modeling language. This work develops effective means of dealing with expressive modeling languages for classical planning. First, we show that expressive languages not only allow simpler problem representations, but also capture additional problem structure that can be leveraged by heuristic solution methods. We develop heuristics that support functions and existential quantification in the problem definition, and show empirically that they can be more informed and cost-effective. Second, we develop a novel width-based algorithm that matches state-of-the-art performance without looking at the declarative representation of actions. This is a significant departure from previous research, and advances the use of expressive modeling languages in planning and the scope and effectiveness of classical planners

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