… We introduce the related preliminaries of RL and brain neuroscience in the “Reinforcement
Learning” and “Brain Neuroscience” sections, respectively. Advanced RL schemes are …

… of model-free reinforcement learning algorithms onto the brain, with the neuromodulator …
More recently, it has been suggested that the brain also employs modelbased methods for …

… theory of reinforcement learning and its … brains of animals and humans bring about complex
behavior. We believe that this connection between neuroscience and reinforcement learning …

… However, in the case of cognitive neuroscientists, this book may be disappointing. From
a cognitive neuroscientific perspective, brain imaging techniques provide tools useful in the …

… reinforcement learning concepts and corresponding work validating their involvement in
animal learning (… To do so, we discuss specific challenges in RL that brain science might hold …

… and model-identified brain networks. Second, as social neuroscience moves forward, it is …
provide neither a thorough overview of reinforcement learning nor an introduction on how to …

… reinforcement learning, whereas reinforcement learning … different types of reinforcement
learning are linked in the brain. We … the neurobiological mechanisms of reinforcement learning. …

… (eg cell, circuit, brain and behavioral levels) and use of different neuroscience techniques (eg
… of using a plain reinforcement learning algorithm as a brain model. Several computational …

… research on brain and … neuroscientists. Our purpose in this review is to call attention to one
such area that has vital implications for neuroscience, namely, deep reinforcement learning (…

… cognitive neuroscience. The success of RL has fed a notion of omniscience that RL can peer
into the brain … Then, we examine where cognitive neuroscience may be overstepping in its …