Towards autonomous neuroprosthetic control using Hebbian reinforcement learning

Objective. Our goal was to design an adaptive neuroprosthetic controller that could learn the mapping from neural states to prosthetic actions and automatically adjust adaptation using only a binary evaluative feedback as a measure of desirability undesirability of performance. Approach. Hebbian rei...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of neural engineering 2013-12, Vol.10 (6), p.066005-15
Hauptverfasser:	Mahmoudi, Babak, Pohlmeyer, Eric A, Prins, Noeline W, Geng, Shijia, Sanchez, Justin C
Format:	Artikel
Sprache:	eng
Schlagworte:	actor-critic Adaptation adaptive control Algorithms Animals Artificial Intelligence - standards associative learning autonomous brain-machine interface Callithrix Control systems Control theory Controllers Feedback Hebbian learning Learning Learning - physiology neural decoding Neural Prostheses - standards neuroprosthetic Policies Random Allocation Reinforcement Reinforcement (Psychology) reinforcement learning
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!