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Browsing Congressos (Departament de Tecnologies de la Informació i les Comunicacions) by Author "Jiménez, Sergio"

Browsing Congressos (Departament de Tecnologies de la Informació i les Comunicacions) by Author "Jiménez, Sergio"

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  • Lotinac, Damir; Segovia-Aguas, Javier; Jiménez, Sergio; Jonsson, Anders, 1973- (Association for the Advancement of Artificial Intelligence (AAAI), 2016)
    In many domains generalized plans can only/nbe computed if certain high-level state features,/ni.e. features that capture key concepts to accurately/ndistinguish between states and make good decisions,/nare available. In ...
  • Furelos Blanco, Daniel; Jonsson, Anders, 1973-; Palacios Verdes, Héctor Luis; Jiménez, Sergio (Association for the Advancement of Artificial Intelligence (AAAI) - Congrés ICAPS17, 2018)
    In this paper we describe STP, a novel algorithm for temporal planning. Similar to several existing temporal planners, STP relies on a transformation from temporal planning to classical planning, and constructs a temporal ...
  • Segovia-Aguas, Javier; Jiménez, Sergio; Jonsson, Anders, 1973- (IJCAI, 2017)
    This paper presents a novel approach for generating Context-Free Grammars (CFGs) from small sets of input strings (a single input string in some cases). Our approach is to compile this task into a classical planning ...
  • Segovia-Aguas, Javier; Jiménez, Sergio; Jonsson, Anders, 1973- (Association for the Advancement of Artificial Intelligence (AAAI), 2016)
    Finite State Controllers (FSCs) are an effective way/nto represent sequential plans compactly. By imposing/nappropriate conditions on transitions, FSCs/ncan also represent generalized plans that solve a/nrange of planning ...
  • Segovia-Aguas, Javier; Jiménez, Sergio; Jonsson, Anders, 1973- (Association for the Advancement of Artificial Intelligence (AAAI), 2017)
    In this paper we introduce a novel approach for unsupervised classification of planning instances based on the recent formalism of planning programs. Our approach is inspired by structured prediction in machine learning, ...

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