claude

reinforcement-learning-brain

Obsidian brain for reinforcement learning, covering fundamentals, deep RL, RLHF/RLAIF and preference optimization, evaluation, tooling, and applied best practices.

13 on GitHubby Daniel Agriciv1.1.0Custom licenseupdated 2 months agoreinforcement-learning
/

Plugin reinforcement-learning-brain from marketplace agricidaniel-reinforcement-learning-brain in AgriciDaniel/reinforcement-learning-second-brain. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (1)

  • reinforcement-learning-brain

    Scaffold and operate Reinforcement Learning Brain, a source-cited Obsidian brain for reinforcement learning, covering fundamentals, deep RL, RLHF/RLAIF and preference optimization, evaluation, tooling, and applied best practices. Use when the user says "reinforcement-learning-brain", "Reinforcement

Subagents (6)

  • classic-rl-foundations-curator

    Curator for the classic RL foundations lane of Reinforcement Learning Brain. Use when maintaining source coverage, open questions, canon folds, and deliverables for classic RL foundations. Read-mostly; records findings in the claim and source ledgers.

  • deep-rl-algorithms-curator

    Curator for the deep RL algorithms lane of Reinforcement Learning Brain. Use when maintaining source coverage, open questions, canon folds, and deliverables for deep RL algorithms. Read-mostly; records findings in the claim and source ledgers.

  • evaluation-and-reproducibility-curator

    Curator for the evaluation and reproducibility lane of Reinforcement Learning Brain. Use when maintaining source coverage, open questions, canon folds, and deliverables for evaluation and reproducibility. Read-mostly; records findings in the claim and source ledgers.

  • llm-post-training-and-preference-optimization-curator

    Curator for the LLM post-training and preference optimization lane of Reinforcement Learning Brain. Use when maintaining source coverage, open questions, canon folds, and deliverables for LLM post-training and preference optimization. Read-mostly; records findings in the claim and source ledgers.

  • reinforcement-learning-secretary

    Grounded secretary for Reinforcement Learning Brain. Use for source-cited answers about reinforcement learning (fundamentals, deep RL, RLHF/RLAIF and preference optimization, evaluation, tooling, applied practice), vault maintenance, claim review, and release hygiene. Reads the brain first, cites va

  • tooling-and-engineering-practice-curator

    Curator for the tooling and engineering practice lane of Reinforcement Learning Brain. Use when maintaining source coverage, open questions, canon folds, and deliverables for tooling and engineering practice. Read-mostly; records findings in the claim and source ledgers.

View source on GitHub skool.com

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