This paper presents a model of brain systems underlying reaching in monkeys based on the idea that complex behaviors are built on the basis of a repertoire of motor primitives organized around specific goals (in this case, arm's postures). The architecture of the system is based on an actor-critic reinforcement-learning model, enhanced with an accumulator model for action selection, capable of selecting sensorimotor primitives so as to accomplish a discrimination reaching task that has been used in physiological studies of monkeys' premotor cortex. The results show that the proposed architecture is a first important step towards the construction of a biologically plausible integrated motor-primitive based model of the hierarchical organization of mammals' sensorimotor systems.


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    Titel :

    Integrating reinforcement-learning, accumulator models, and motor-primitives to study action selection and reaching in monkeys


    Beteiligte:
    Ognibene, D (Autor:in) / Mannella, F (Autor:in) / Pezzulo, G (Autor:in) / Baldassarre, G (Autor:in)

    Erscheinungsdatum :

    2006-01-01


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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