کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
411147 | 679182 | 2009 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A reinforcement learning based neural network architecture for obstacle avoidance in multi-fingered grasp synthesis
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
The ability to learn from interaction with the exterior world as well as variability are two main features of living organisms. The aim of this study is to present and discuss the property of a stochastic reinforcement learning based model of upper limb posture generation that exhibits both properties. The capacity of the model to discover suitable postures satisfying task and obstacle avoidance constraints is demonstrated by simulation. Also, task equivalent configurations that can be linked to recent findings in the motor control literature are generated by the proposed formalism due to its stochastic nature.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 72, Issues 4–6, January 2009, Pages 1229–1241
Journal: Neurocomputing - Volume 72, Issues 4–6, January 2009, Pages 1229–1241
نویسندگان
Nasser Rezzoug, Philippe Gorce,