{ "dc.contributor.author": "Carreras Pérez, Marc" , "dc.contributor.author": "Ridao Rodríguez, Pere" , "dc.contributor.author": "Batlle i Grabulosa, Joan" , "dc.contributor.author": "Nicosevici, Tudor" , "dc.date.accessioned": "2010-05-05T11:38:43Z" , "dc.date.available": "2010-05-03T15:06:24Z" , "dc.date.available": "2010-05-05T11:38:43Z" , "dc.date.issued": "2002" , "dc.identifier.citation": "Carreras, M., Ridao, P. , Batlle, J., i Nicosevici, T. (2002). Efficient learning of reactive robot behaviors with a Neural-Q_learning approach. IEEE/RSJ International Conference on Intelligent Robots and Systems, 1, 1020-1025. Recuperat 05 maig 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1041525" , "dc.identifier.isbn": "0-7803-7398-7" , "dc.identifier.uri": "http://hdl.handle.net/10256/2163" , "dc.description.abstract": "The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed" , "dc.format.mimetype": "application/pdf" , "dc.language.iso": "eng" , "dc.publisher": "IEEE" , "dc.relation.isformatof": "Reproducció digital del document publicat a: http://dx.doi.org/10.1109/IRDS.2002.1041525" , "dc.relation.ispartof": "© IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002, vol. 1, p. 1020-1025" , "dc.relation.ispartofseries": "Articles publicats (D-ATC)" , "dc.rights": "Tots els drets reservats" , "dc.subject": "Intel·ligència artificial" , "dc.subject": "Robots mòbils" , "dc.subject": "Xarxes neuronals (Informàtica)" , "dc.subject": "Artificial intelligence" , "dc.subject": "Neural networks (Computer science)" , "dc.subject": "Mobile robots" , "dc.title": "Efficient learning of reactive robot behaviors with a Neural-Q_learning approach" , "dc.type": "info:eu-repo/semantics/article" , "dc.rights.accessRights": "info:eu-repo/semantics/openAccess" , "dc.identifier.doi": "http://dx.doi.org/10.1109/IRDS.2002.1041525" }