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RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari

Por um escritor misterioso

Descrição
In this issue, we look at MuZero, DeepMind’s new algorithm that learns a model and achieves AlphaZero performance in Chess, Shogi, and Go and achieves state-of-the-art performance on Atari. We also look at Safety Gym, OpenAI’s new environment suite for safe RL.
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Applied Sciences, Free Full-Text
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
RL Weekly 32: New SotA Sample Efficiency on Atari and an Analysis of the Benefits of Hierarchical RL
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Superhuman Performance on the Atari 100K Benchmark: The Power of BBF - A New Value-Based RL Agent from Google DeepMind, Mila, and Universite de Montreal - MarkTechPost
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
State of AI Report 2023 - Air Street Capital
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Applied Sciences, Free Full-Text
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
PDF) OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Mastering Atari Games with Limited Data – arXiv Vanity
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Atari 2600 Kangaroo Benchmark (Atari Games)
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Johan Gras (@gras_johan) / X
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