reviewNeural NetworksApr 19, 2022HYBRID OA

Deep learning, reinforcement learning, and world models

The University of Tokyo · Meta (Israel) · +10 more institutions

PubMed
Indexed incrossrefpubmed

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…

Citation impact

482
total citations
FWCI
59.24
Percentile
100%
References
96
Citations per year

Authors

8

Topics & keywords

Keywords
  • Reinforcement learning
  • Artificial intelligence
  • Computer science
  • Session (web analytics)
  • Human intelligence
  • Deep learning
  • Cognitive science
  • Reinforcement
UN Sustainable Development Goals
  • Quality Education
No related works found for this paper.