The Prefrontal Cortex as a Meta-Reinforcement Learning System
Explore the concept of the prefrontal cortex as a meta-reinforcement learning system in this 55-minute lecture by Matthew Botvinick from DeepMind Technologies Limited and University College London. Delve into computational theories of the brain, covering topics such as recurrent neural networks, neuroscience and AI, and learning to learn. Examine the connections between Brendan Lake's work on Atari games and background knowledge, and investigate the differences between learning and inference. Analyze various neural network architectures, including multilayer perceptrons and recurrent neural networks, and their applications to bandit problems and Harlow's task. Discover insights from neuroscience research on hippocampal amnesia and the inferred value effect. Gain a comprehensive understanding of how these concepts contribute to a virtuous circle of collaboration between AI and neuroscience.