25 lines
725 B
Markdown
25 lines
725 B
Markdown
# Agentic Learner Loop
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The agentic learner loop is the first closed-loop prototype for AI-student behavior in Didactopus.
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## Current loop
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1. Inspect current mastery state
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2. Ask graph-aware planner for next best concept
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3. Produce synthetic attempt
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4. Score attempt into evidence
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5. Update mastery state
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6. Repeat until target is reached or iteration budget ends
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## Important limitation
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The current implementation is a scaffold. The learner attempt is synthetic and deterministic, not a true external model call with robust domain evaluation.
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## Why it still matters
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It establishes the orchestration pattern for:
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- planner-guided concept selection
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- evidence accumulation
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- mastery updates
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- goal-directed progression
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