RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Por um escritor misterioso
Last updated 20 setembro 2024
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.
PDF) Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems
Scheduling UAV Swarm with Attention-based Graph Reinforcement Learning for Ground-to-air Heterogeneous Data Communication
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Applied Sciences, Free Full-Text
Warm-start Reinforcement Learning Mobility Science Automation and Inclusion Center
Atari 2600 Kangaroo Benchmark (Atari Games)
Johan Gras (@gras_johan) / X
RL Weekly
PDF) Mastering Atari Games with Limited Data
All Categories - Miles Brundage
Summaries from arXiv e-Print archive on
Denis Yarats on X: Impressive improvements in data-efficiency on Atari 100K, shattering our month old SOTA results from DrQ! Glad to see that some of our ideas ended up being useful in
PDF) OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments
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