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docs: improve README with usage instructions
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README.md
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# 🧪 Morphogen Gradients
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Explore
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##
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## How It Works
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The
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# 🧪 Morphogen Gradients
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Explore gradient-based agent coordination where six chemical signals guide behavior without a central controller -- like morphogen gradients directing cell differentiation in developing embryos.
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## What to Try
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1. Open the **Manual Gradient** tab, adjust the six morphogen sliders (complexity, confidence, budget, error_rate, urgency, risk), and click **Analyze** to see strategy hints and phenotype adaptation.
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2. Switch to the **Orchestrator Simulation** tab, pick a preset (e.g. "Crisis mode" or "Cascading failures"), and click **Run Simulation** to watch gradients evolve step-by-step as the orchestrator reacts.
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3. Try "Budget crunch" to see how low budget signals change the agent's strategy, then compare with "Easy task" where all signals are favorable.
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## How It Works
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The MorphogenGradient holds six signal types that the GradientOrchestrator adjusts after each step based on outcomes. These signals produce strategy hints and phenotype parameters that shape agent behavior -- enabling decentralized coordination without explicit orchestration rules.
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## Learn More
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[GitHub](https://github.com/coredipper/operon) | [PyPI](https://pypi.org/project/operon-ai/) | [Paper](https://github.com/coredipper/operon/tree/main/article)
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requirements.txt
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gradio>=4.0
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operon-ai>=0.
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gradio>=4.0
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operon-ai>=0.15.0
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