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
UC Berkeley Reward-Free RL Beats SOTA Reward-Based RL
PDF) Tensor Implementation of Monte-Carlo Tree Search for Model-Based Reinforcement Learning
PDF) OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments
PDF) Alpha-T: Learning to Traverse over Graphs with An AlphaZero-inspired Self-Play Framework
RL Weekly 37: Observational Overfitting, Hindsight Credit Assignment, and Procedurally Generated Environment Suite
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Memory for Lean Reinforcement Learning.pdf
Atari 2600 Kangaroo Benchmark (Atari Games)
PDF) Mastering Atari Games with Limited Data
UC Berkeley Reward-Free RL Beats SOTA Reward-Based RL
Aman's AI Journal • Papers List
State of AI Report 2023 - Air Street Capital
Memory-based Reinforcement Learning
Aman's AI Journal • Papers List
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