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Reflexion(RX)
Agents learn from experience through verbal self-reflection and episodic memory
In 30 seconds
- What
- Agent runs a task, reflects on failure in natural language, stores the reflection, and uses it to improve the next attempt without retraining.
- When to use
- Tasks where the agent can fail safely, learn from mistakes, and retry; failures contain actionable signals the agent can articulate.
- Watch out
- Reflection quality depends entirely on the agent's ability to diagnose root causes; vague or incorrect self-analysis compounds errors across trials.
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Reflexion: Overview
Agents learn from experience through verbal self-reflection and episodic memory
- Verbal reinforcement learning
- Episodic memory integration
- Learning from failures
- No fine-tuning required
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References
The papers, specifications, and repositories this pattern is based on.
- Reflexion: Language Agents with Verbal Reinforcement Learning (Shinn et al., 2023)arXiv:2303.11366
- ReAct: Synergizing Reasoning and Acting in Language Models (Yao et al., 2023)arXiv:2210.03629
- Self-Refine: Iterative Refinement with Self-Feedback (Madaan et al., 2023)arXiv:2303.17651
- Teaching Large Language Models to Self-Debug (Chen et al., 2023)arXiv:2304.05128
- Reflexion reference implementation
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