Integrating reinforcement-learning, accumulator models and motor-primitives to study action selection and researching in monkeys.
Contributo in Atti di convegno
Data di Pubblicazione:
2006
Abstract:
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.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Reinforcement learning; models
Elenco autori:
Baldassarre, Gianluca; Mannella, Francesco
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