gbanyan
43c025e060
- Add complete experiments directory with pilot study infrastructure - 5 experimental conditions (direct, expert-only, attribute-only, full-pipeline, random-perspective) - Human assessment tool with React frontend and FastAPI backend - AUT flexibility analysis with jump signal detection - Result visualization and metrics computation - Add novelty-driven agent loop module (experiments/novelty_loop/) - NoveltyDrivenTaskAgent with expert perspective perturbation - Three termination strategies: breakthrough, exhaust, coverage - Interactive CLI demo with colored output - Embedding-based novelty scoring - Add DDC knowledge domain classification data (en/zh) - Add CLAUDE.md project documentation - Update research report with experiment findings Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
24 lines
670 B
Python
24 lines
670 B
Python
"""
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Condition implementations for the 5-condition experiment.
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C1: Direct generation (baseline)
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C2: Expert-only (no attributes)
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C3: Attribute-only (no experts)
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C4: Full pipeline (attributes + experts)
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C5: Random-perspective (random words instead of experts)
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"""
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from .c1_direct import generate_ideas as c1_generate
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from .c2_expert_only import generate_ideas as c2_generate
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from .c3_attribute_only import generate_ideas as c3_generate
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from .c4_full_pipeline import generate_ideas as c4_generate
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from .c5_random_perspective import generate_ideas as c5_generate
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__all__ = [
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"c1_generate",
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"c2_generate",
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"c3_generate",
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"c4_generate",
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"c5_generate",
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]
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