Structure and inference in classical planning

Classical planning is the problem of finding a sequence of actions for achieving a goal from an initial state assuming that actions have deterministic effects. The most effective approach for finding such plans is based on heuristic search guided by heuristics extracted automatically from the proble...

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Bibliographic Details
Main Author: Lipovetzky, Nir
Other Authors: Geffner, Héctor
Format: Doctoral Thesis
Language:English
Published: Universitat Pompeu Fabra 2012
Subjects:
62
Online Access:http://hdl.handle.net/10803/101416
Description
Summary:Classical planning is the problem of finding a sequence of actions for achieving a goal from an initial state assuming that actions have deterministic effects. The most effective approach for finding such plans is based on heuristic search guided by heuristics extracted automatically from the problem representation. In this thesis, we introduce alternative approaches for performing inference over the structure of planning problems that do not appeal to heuristic functions, nor to reductions to other formalisms such as SAT or CSP. We show that many of the standard benchmark domains can be solved with almost no search or a polynomially bounded amount of search, once the structure of planning problems is taken into account. In certain cases we can characterize this structure in terms of a novel width parameter for classical planning. === Los problemas en planificación clásica consisten en encontrar la secuencia de acciones que lleve a un agente a su objetivo desde un estado inicial, asumiendo que los efectos de las acciones son determinísticos. El enfoque más efectivo para encontrar dichos planes es la búsqueda heurística, extrayendo de la representación del problema de forma automática heurísticas que guien la búsqueda. En esta tesis, introducimos enfoques alternativos para realizar inferencias sobre la estructura del los problemas de planificación, sin apelar a funciones heurísticas, reducciones a SAT o CSP. Demostramos que la mayoría de problemas estándares pueden ser resueltos casi sin búsqueda o con una cantidad de búsqueda polinomialmente limitada, en algunos casos, caracterizando la estructura de los problemas en término de un nuevo parámetro de complejidad para la planificación clásica.