• Learning probabilistic action models from interpretation transitions 

    Martínez Martínez, David; Ribeiro, Tony; Inoue, Katsumi; Alenyà Ribas, Guillem; Torras, Carme (2015)
    Texto en actas de congreso
    Acceso abierto
    Probabilistic planners are very flexible tools that provide good solutions for difficult tasks. However, they rely on a model of the domain and actions, which they have difficulties to learn for complex tasks. We propose ...
  • Learning relational dynamics of stochastic domains for planning 

    Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme; Ribeiro, Tony; Inoue, Katsumi (2016)
    Texto en actas de congreso
    Acceso abierto
    Probabilistic planners are very flexible tools that can provide good solutions for difficult tasks. However, they rely on a model of the domain, which may be costly to either hand code or automatically learn for complex ...
  • Relational reinforcement learning for planning with exogenous effects 

    Martinez Martinez, David; Alenyà Ribas, Guillem; Ribeiro, Tony; Inoue, Katsumi; Torras, Carme (2017)
    Artículo
    Acceso abierto
    Probabilistic planners have improved recently to the point that they can solve difficult tasks with complex and expressive models. In contrast, learners cannot tackle yet the expressive models that planners do, which forces ...