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OpenClaw-RL: Personalizing AI Agents from Conversation Feedback

How to make your AI assistant learn your preferences from natural conversations. Build the full OpenClaw-RL pipeline: session-aware rollouts, Binary RL with GRPO-TCR, On-Policy Distillation with hindsight hints, and the RLAnything closed loop.

intermediate~4 hours4 notebooksOpenClaw-RLPersonalizationGRPO-TCROn-Policy DistillationProcess Reward ModelRLAnythingConversation RL

Curator of this Module

Dr. Rajat Dandekar

Dr. Rajat Dandekar

Course Instructor

Dr. Rajat Dandekar is a researcher and educator specializing in AI/ML, with a passion for making complex concepts accessible through intuitive explanations and hands-on learning.

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Learning Path

Article
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Notebook 1
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Notebook 2
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Notebook 3
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Notebook 4
Case Study
Certificate