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April 19, 2022Neural Networks530 citationsOpen Access

Deep learning, reinforcement learning, and world models

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YMYutaka MatsuoYLYann LeCunMSManeesh Sahani

Key Points

  • The review aims to explore the connections between deep learning, reinforcement learning, and human intelligence.
  • Summarizes discussions from the International Symposium on Artificial Intelligence and Brain Science.
  • Highlights recent studies related to deep learning and reinforcement learning technologies.
  • Identified key technologies that may lead to human-level intelligence.
  • Discussed insights from neuroscientific findings in relation to AI methods.

Abstract

Deep learning (DL) and reinforcement learning (RL) methods seem to be a part of indispensable factors to achieve human-level or super-human AI systems. On the other hand, both DL and RL have strong connections with our brain functions and with neuroscientific findings. In this review, we summarize talks and discussions in the "Deep Learning and Reinforcement Learning" session of the symposium, International Symposium on Artificial Intelligence and Brain Science. In this session, we discussed whether we can achieve comprehensive understanding of human intelligence based on the recent advances of deep learning and reinforcement learning algorithms. Speakers contributed to provide talks about their recent studies that can be key technologies to achieve human-level intelligence.

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Cite This Study

Matsuo et al. (2022) studied this question.

synapsesocial.com/papers/69d8fc312c87b79b92d18a75https://doi.org/10.1016/j.neunet.2022.03.037
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