RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
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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.
deep learning – Severely Theoretical
PDF) OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments
Johan Gras (@gras_johan) / X
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RL Weekly 9: Sample-efficient Near-SOTA Model-based RL, Neural MMO, and Bottlenecks in Deep Q-Learning
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Atari 2600 Kangaroo Benchmark (Atari Games)
RL Weekly 9: Sample-efficient Near-SOTA Model-based RL, Neural MMO, and Bottlenecks in Deep Q-Learning
Summaries from arXiv e-Print archive on
PDF) Alpha-T: Learning to Traverse over Graphs with An AlphaZero-inspired Self-Play Framework
RL Weekly
Memory for Lean Reinforcement Learning.pdf
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