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.
Summaries from arXiv e-Print archive on
Applied Sciences, Free Full-Text
deep learning – Severely Theoretical
RL Weekly 9: Sample-efficient Near-SOTA Model-based RL, Neural MMO, and Bottlenecks in Deep Q-Learning : r/reinforcementlearning
PDF) On Reinforcement Learning for the Game of 2048
RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Applied Sciences, Free Full-Text
Kristian Kersting
2008.06495] Joint Policy Search for Multi-agent Collaboration with Imperfect Information
Mastering Atari Games with Limited Data – arXiv Vanity
All Categories - Miles Brundage
Scheduling UAV Swarm with Attention-based Graph Reinforcement Learning for Ground-to-air Heterogeneous Data Communication
Kristian Kersting
Mastering Atari Games with Limited Data – arXiv Vanity