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دسته بندی:
یادگیری تقویتی - Reinforcement-Learning
سال انتشار:
2020
عنوان انگلیسی مقاله:
Deep Reinforcement Learning and Its Neuroscientific Implications
ترجمه فارسی عنوان مقاله:
یادگیری تقویتی عمیق و پیامدهای عصبی علمی آن
منبع:
Sciencedirect - Elsevier - Neuron, 107 (2020) 603-616. doi:10.1016/j.neuron.2020.06.014
نویسنده:
Matthew Botvinick,1,2,* Jane X. Wang,1 Will Dabney,1 Kevin J. Miller,1,2 and Zeb Kurth-Nelson1,2
چکیده انگلیسی:
The emergence of powerful artificial intelligence (AI) is defining new research directions in neuroscience. To
date, this research has focused largely on deep neural networks trained using supervised learning in tasks
such as image classification. However, there is another area of recent AI work that has so far received less
attention from neuroscientists but that may have profound neuroscientific implications: deep reinforcement
learning (RL). Deep RL offers a comprehensive framework for studying the interplay among learning, representation,
and decision making, offering to the brain sciences a new set of research tools and a wide range of
novel hypotheses. In the present review, we provide a high-level introduction to deep RL, discuss some of its
initial applications to neuroscience, and survey its wider implications for research on brain and behavior,
concluding with a list of opportunities for next-stage research.
قیمت: رایگان
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