reinforcement learning: 41 curated resources
reinforcement learning
41 resources · page 2 of 2
Jumanji
Jumanji documentation: InstaDeep's suite of JAX reinforcement-learning environments for combinatorial and decision problems.
MuZero
by Julian Schrittwieser et al. (Google DeepMind)
arXiv paper (2019) introducing MuZero, planning with a learned model to master Atari, Go, chess and shogi.
OpenAI Five (Dota 2)
by OpenAI
arXiv paper (2019) "Dota 2 with Large Scale Deep Reinforcement Learning", describing OpenAI Five's large-scale reinforcement learning for Dota 2.
PPO
by John Schulman et al. (OpenAI)
arXiv paper (2017) "Proximal Policy Optimization Algorithms", introducing PPO, a policy gradient method with a clipped surrogate objective.
RL4CO
RL4CO documentation: reinforcement-learning benchmark and library for combinatorial optimisation problems.
SAC
by Tuomas Haarnoja et al. (UC Berkeley)
arXiv paper (2018) introducing Soft Actor-Critic (SAC), off-policy maximum-entropy deep reinforcement learning.
verifiers v1
Prime Intellect post on verifiers v1, splitting environments into tasksets, harnesses and runtimes for agentic RL and evals.
EASA AI Concept Paper Proposed Issue 03
by European Union Aviation Safety Agency (EASA)
EASA AI Concept Paper Proposed Issue 03 (PDF), extending aviation AI assurance guidance to more methods and Level 3 automation.
Reward Hacking in Reinforcement Learning (Lil'Log)
by Lilian
Lilian Weng's survey of reward hacking in reinforcement learning, including in RLHF and coding tasks.