با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
---|---|---|
1 |
Mutual benefits: Combining reinforcement learning with sequential sampling models
مزایای متقابل: تلفیق یادگیری تقویتی با مدلهای نمونه برداری متوالی-2020 Reinforcement learning models of error-driven learning and sequential-sampling models of decision making have
provided significant insight into the neural basis of a variety of cognitive processes. Until recently, model-based
cognitive neuroscience research using both frameworks has evolved separately and independently. Recent efforts
have illustrated the complementary nature of both modelling traditions and showed how they can be integrated
into a unified theoretical framework, explaining trial-by-trial dependencies in choice behavior as well as
response time distributions. Here, we review a theoretical background of integrating the two classes of models,
and review recent empirical efforts towards this goal. We furthermore argue that the integration of both
modelling traditions provides mutual benefits for both fields, and highlight promises of this approach for
cognitive modelling and model-based cognitive neuroscience. Keywords: Sequential sampling models | Reinforcement learning | Instrumental learning | Decision-making |
مقاله انگلیسی |