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The agent critically evaluates its own intermediate results and uses this feedback to improve the next steps or output in iterative loops. Typical conditions for use: Result quality takes precedence over minimal latency; Errors can be identified by the model through targeted self-critique. The central trade-off: Leads to higher result quality, but incurs add…
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Theoretical construct: explains a term, principle, or mental model.
What organizes, connects, or makes decisions possible.
Reflexion is an agent method that uses verbal feedback as episodic memory for later attempts.
Noah Shinn and co-authors introduced Reflexion in 2023 for language agents: feedback is turned into text and stored instead of changing model weights after every attempt.
An actor attempts a task, an evaluator provides feedback, and a reflection step formulates a lesson. The next attempt receives that lesson from episodic memory.
The term captures this component’s central purpose and key decision.
The component connects clear information with a verifiable decision or action.
Application context, responsibilities, limits, and evidence determine practical quality.
Reflexion gives language agents a compact lesson from earlier failures and suits multi-step tasks with observable feedback. Episodic memory can propagate false lessons and grow without bounds.
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