论文标题
强化学习及其与神经科学和心理学的联系
Reinforcement Learning and its Connections with Neuroscience and Psychology
论文作者
论文摘要
强化学习方法最近在执行复杂的顺序任务上非常成功，例如玩Atari游戏，Go and Poker。这些算法仅利用与环境互动获得的标量奖励，在几个任务中超过了几个任务的表现。虽然当然有大量独立创新来产生这种结果，但强化学习中的许多核心思想都受到动物学习，心理学和神经科学现象的启发。在本文中，我们全面回顾了神经科学和心理学中的大量发现，这些发现证明了强化学习是在大脑中建模学习和决策的有前途的候选人。在此过程中，我们在神经生理和行为文献中的各种现代RL算法和特定发现之间构建了映射。然后，我们讨论RL，神经科学与心理学之间这种观察到的关系的含义及其在AI和脑科学中的研究中的作用。
Reinforcement learning methods have recently been very successful at performing complex sequential tasks like playing Atari games, Go and Poker. These algorithms have outperformed humans in several tasks by learning from scratch, using only scalar rewards obtained through interaction with their environment. While there certainly has been considerable independent innovation to produce such results, many core ideas in reinforcement learning are inspired by phenomena in animal learning, psychology and neuroscience. In this paper, we comprehensively review a large number of findings in both neuroscience and psychology that evidence reinforcement learning as a promising candidate for modeling learning and decision making in the brain. In doing so, we construct a mapping between various classes of modern RL algorithms and specific findings in both neurophysiological and behavioral literature. We then discuss the implications of this observed relationship between RL, neuroscience and psychology and its role in advancing research in both AI and brain science.
