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Reflexion Actor
The Reflexion Actor is a cognitive AI architecture that enhances an agent's ability to learn from its mistakes through self-reflection. It combines a base reasoning model (the Actor) with a memory mechanism and a critic loop that evaluates performance after each task attempt.
Instead of blindly retrying tasks, the Reflexion Actor:
- Logs thoughts and actions taken during a task
- Reflects on failed attempts by identifying what went wrong
- Updates its future reasoning by revising strategies or tools used
This feedback loop turns the agent into a continual learner — it performs, evaluates, and improves, making it more sample-efficient and resilient than traditional single-shot agents. Reflexion can be layered with ReAct or other planning systems to further boost its reasoning capability.
