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# Reinforcement Learning

[Beginner](/levels/beginner/index.md) [Intermediate](/levels/intermediate/index.md) [Advanced](/levels/advanced/index.md) [Expert](/levels/expert/index.md)

41 resources · page 2 of 2

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### [Jumanji](/foundations/llm-fundamentals/jumanji/index.md)

Creator not supplied; see original source.

Jumanji documentation: InstaDeep's suite of JAX reinforcement-learning environments for combinatorial and decision problems.

Advanced · unknown · unknown resource · en 

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### [MuZero](/foundations/llm-fundamentals/muzero/index.md)

Creator not supplied; see original source.

arXiv paper (2019) introducing MuZero, planning with a learned model to master Atari, Go, chess and shogi.

Advanced–Expert · unknown · unknown resource · en 

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### [OpenAI Five (Dota 2)](/foundations/llm-fundamentals/openai-five-dota-2/index.md)

Creator not supplied; see original source.

arXiv paper (2019) "Dota 2 with Large Scale Deep Reinforcement Learning", describing OpenAI Five's large-scale reinforcement learning for Dota 2.

Advanced–Expert · unknown · unknown resource · en 

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### [PPO](/foundations/llm-fundamentals/ppo/index.md)

Creator not supplied; see original source.

arXiv paper (2017) "Proximal Policy Optimization Algorithms", introducing PPO, a policy gradient method with a clipped surrogate objective.

Advanced–Expert · unknown · unknown resource · en 

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### [RL4CO](/foundations/llm-fundamentals/rl4co/index.md)

Creator not supplied; see original source.

RL4CO documentation: reinforcement-learning benchmark and library for combinatorial optimisation problems.

Advanced · unknown · unknown resource · en 

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### [SAC](/foundations/llm-fundamentals/sac/index.md)

Creator not supplied; see original source.

arXiv paper (2018) introducing Soft Actor-Critic (SAC), off-policy maximum-entropy deep reinforcement learning.

Advanced–Expert · unknown · unknown resource · en 

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### [verifiers v1](/foundations/llm-fundamentals/verifiers-v1/index.md)

Creator not supplied; see original source.

Prime Intellect post on verifiers v1, splitting environments into tasksets, harnesses and runtimes for agentic RL and evals.

Advanced · unknown · unknown resource · en 

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### [EASA AI Concept Paper Proposed Issue 03](/foundations/llm-fundamentals/easa-ai-concept-paper-proposed-issue-03/index.md)

Creator not supplied; see original source.

EASA AI Concept Paper Proposed Issue 03 (PDF), extending aviation AI assurance guidance to more methods and Level 3 automation.

Expert · unknown · unknown resource · en 

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### [Reward Hacking in Reinforcement Learning (Lil'Log)](/foundations/llm-fundamentals/lilian-weng-reward-hacking-in-rl/index.md)

Creator not supplied; see original source.

Lilian Weng's survey of reward hacking in reinforcement learning, including in RLHF and coding tasks.

Expert · unknown · unknown resource · en 

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