Now showing items 1-20 of 23

    • A competitive strategy for function approximation in Q-learning 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (2011)
      Conference report
      Open Access
      In this work we propose an approach for generalization in continuous domain Reinforcement Learning that, instead of using a single function approximator, tries many different function approximators in parallel, each one ...
    • A relational positioning methodology for robot task specification and execution 

      Rodríguez Tsouroukdissian, Adolfo; Basañez Villaluenga, Luis; Celaya Llover, Enric (IEEE, 2008)
      Article
      Open Access
      This paper presents a relational positioning methodology that allows to restrict totally or partially the movements of an object by specifying its allowed positions in terms of a set of intuitive geometric constraints. In ...
    • Action rule induction from cause-effect pairs learned through robot-teacher interaction 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric; Torras, Carme; Wörgötter, Florentin (University of Karlsruhe, 2008)
      Conference report
      Open Access
      In this work we propose a decision-making system that efficiently learns behaviors in the form of rules using natural human instructions about cause-effect relations in currently observed situations, avoiding complicated ...
    • Action rule induction from cause-effect pairs learned through robot-teacher interaction 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric; Torras, Carme; Wörgötter, Florentin (2008)
      Conference report
      Open Access
      In this work we propose a decision-making system that efficiently learns behaviors in the form of rules using natural human instructions about cause-effect relations in currently observed situations, avoiding complicated ...
    • Competitive function approximation for reinforcement learning 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (2014)
      External research report
      Open Access
      The application of reinforcement learning to problems with continuous domains requires representing the value function by means of function approximation. We identify two aspects of reinforcement learning that make the ...
    • Description of a robotics-oriented relational positioning methodology 

      Rodríguez Tsouroukdissian, Adolfo; Basañez Villaluenga, Luis; Celaya Llover, Enric (2007-09)
      External research report
      Open Access
      This paper presents a relational positioning methodology for flexibly and intuitively specifying offline programmed robot tasks, as well as for assisting the execution of teleoperated tasks demanding precise movements. In ...
    • Exact interval propagation for the efficient solution of planar linkages 

      Celaya Llover, Enric; Creemers, Tom Lambert; Ros Giralt, Lluís (ASME, 2007)
      Conference report
      Open Access
      This paper presents an interval propagation algorithm for variables in single-loop linkages. Given allowed intervals of values for all variables, the algorithm provides, for every variable, the exact interval of values for ...
    • Exact interval propagation for the efficient solution of position analysis problems on planar linkages 

      Celaya Llover, Enric; Creemers, Tom Lambert; Ros Giralt, Lluís (2012)
      Article
      Open Access
      This paper presents an interval propagation algorithm for variables in planar single-loop linkages. Given intervals of allowed values for all variables, the algorithm provides, for every variable, the whole set of values, ...
    • Learning rules from cause-effects explanations 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric; Torras, Carme; Wörgötter, Florentin (2008)
      External research report
      Open Access
      In this work we propose a learning system to learn on-line an action policy coded in rules using natural human instructions about cause-effect relations in currently observed situations. The instructions only on currently ...
    • Natural landmark detection for visually-guided robot navigation 

      Celaya Llover, Enric; Albarral, José L.; Jimenez Schlegl, Pablo; Torras, Carme (Springer, 2007)
      Part of book or chapter of book
      Open Access
      The main difficulty to attain fully autonomous robot navigation outdoors is the fast detection of reliable visual references, and their subsequent characterization as landmarks for immediate and unambiguous recognition. ...
    • Natural landmark detection for visually-guided robot navigation 

      Celaya Llover, Enric; Albarral Garcia, Jose Luis; Jimenez Schlegl, Pablo; Torras, Carme (2007)
      Conference report
      Open Access
      The main difficulty to attain fully autonomous robot navigation outdoors is the fast detection of reliable visual references, and their subsequent characterization as landmarks for immediate and unambiguous recognition. ...
    • On-line learning of macro planning operators using probabilistic estimations of cause-effects 

      Agostini, Alejandro Gabriel; Wörgötter, Florentin; Celaya Llover, Enric; Torras, Carme (2008)
      External research report
      Open Access
      In this work we propose an on-line learning method for learning action rules for planning. The system uses a probabilistic approach of a constructive induction method that combines a beam search with an example-based search ...
    • Online EM with weight-based forgetting 

      Celaya Llover, Enric; Agostini, Alejandro Gabriel (2015)
      Article
      Open Access
      In the on-line version of the EM algorithm introduced by Sato and Ishii (2000), a time-dependent discount factor is introduced for forgetting the effect of the old posterior values obtained with an earlier, inaccurate ...
    • Online reinforcement learning using a probability density estimation 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (The MIT Press. Massachusetts Institute of Technology, 2017-01-01)
      Article
      Open Access
      Function approximation in online, incremental, reinforcement learning needs to deal with two fundamental problems: biased sampling and nonstationarity. In this kind of task, biased sampling occurs because samples are ...
    • Probability density estimation of the Q Function for reinforcement learning 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (2009)
      External research report
      Open Access
      Performing Q-Learning in continuous state-action spaces is a problem still unsolved for many complex applications. The Q function may be rather complex and can not be expected to fit into a predefined parametric model. In ...
    • Reinforcement learning for robot control using probability density estimations 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (INSTICC Press. Institute for Systems and Technologies of Information, Control and Communication, 2010)
      Conference report
      Restricted access - publisher's policy
      The successful application of Reinforcement Learning (RL) techniques to robot control is limited by the fact that, in most robotic tasks, the state and action spaces are continuous, multidimensional, and in essence, too ...
    • Reinforcement learning with a Gaussian mixture model 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (2010)
      Conference report
      Open Access
      Recent approaches to Reinforcement Learning (RL) with function approximation include Neural Fitted Q Iteration and the use of Gaussian Processes. They belong to the class of fitted value iteration algorithms, which use a ...
    • Robot task specification and execution through relational positioning 

      Rodríguez Tsouroukdissian, Adolfo; Basañez Villaluenga, Luis; Celaya Llover, Enric (IFAC, 2007)
      Conference report
      Open Access
      This paper presents a relational positioning methodology for flexibly and intuitively specifying offline programmed robot tasks, and for assisting the execution of teleoperated tasks featuring precise or repetitive movements. ...
    • Solution intervals for variables in spatial RCRCR linkages 

      Celaya Llover, Enric (2019-03-01)
      Article
      Open Access
      An analytic method to compute the solution intervals for the input variables of spatial RCRCR linkages and their inversions is presented. The input-output equation is formulated as the intersection of a single ellipse with ...