Human Level Control Through Deep Reinforcement Learning
Olivia Luz
Human level control through deep reinforcement learning abstract the theory of reinforcement learning provides a normative account deeply rooted in psychological and neuroscientific perspectives on animal behaviour of how agents may optimize their control of an environment.
Remarkably humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. Arxiv 2013 7 atari games the first step towards general artificial intelligence deepmind got acquired by google 2014 human level control through deep reinforcement learning. Playing atari with deep reinforcement learning. The theory of reinforcement learning provides a normative account deeply rooted in psychological and neuroscientific perspectives on animal behaviour of how agents may optimize their control of an environment.
Human level control through deep reinforcement learning nature14236 pdf created date. Nature 2015 49 atari games google patented deep reinforcement learning. Bellemare 1 alex graves 1. Rusu 1 joel veness 1 marc g.
The theory of reinforcement learning provides a normative account deeply rooted in psychological and neuroscientific perspectives on animal behaviour of how agents may optimize their control of an environment. While reinforcement learning agents have achieved some successes in a variety of domains their applicability has previously been. Request pdf human level control through deep reinforcement learning the theory of reinforcement learning provides a normative account deeply rooted in psychological and neuroscientific. Human level control through deep reinforcement learning.
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