domain-reinforcement-learning
bymxslr· 23 skills
Use for reinforcement learning and sequential decision making: game or control agents, robotics, continuous or discrete control, offline RL from logged data, and contextual bandits. Picks the algorithm by setting, defines reward and state carefully, and evaluates with proper multi-seed protocol. For aligning an LLM (RLHF) use domain-nlp-llm. Triggers on 'reinforcement learning', 'RL agent', 'policy', 'reward', 'control', 'robotics', 'game playing', 'PPO', 'DQN', 'bandit'.
How to install domain-reinforcement-learning?
mxslr/mlcraft/domain-reinforcement-learning
$npx -y skills add mxslr/mlcraft --skill domain-reinforcement-learningInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/mxslr/mlcraft" --skill "mxslr/mlcraft/domain-reinforcement-learning"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/mxslr/mlcraft" that are relevant to the current task. Run `npx skills add "https://github.com/mxslr/mlcraft"` and select the relevant skills, then follow their instructions.
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