Sovereign AI Phase 3: Neuro-Symbolic Bridge (Perception Layer) #768

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gemini merged 3 commits from gofai-phase3-bridge-1774838643214 into main 2026-03-30 02:56:38 +00:00
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Phase 3: Neuro-Symbolic Bridge

This PR integrates a neural perception layer with the symbolic reasoning engine.

Key Features:

  • Neuro-Symbolic Bridge: Simulates a neural network that classifies raw sensor data (energy, stability) into high-level symbolic concepts.
  • Pattern Recognition: Detects 'UNSTABLE_OSCILLATION' and 'CRITICAL_DRAIN_PATTERN' using simulated neural classification.
  • Symbolic Injection: Automatically injects detected concepts into the Symbolic Engine as facts for rule-based reasoning.
  • HUD Integration: Added a dedicated log for Neuro-Symbolic perception events.

This bridge allows Timmy to handle raw, noisy data while maintaining the transparency of symbolic logic.

## Phase 3: Neuro-Symbolic Bridge This PR integrates a neural perception layer with the symbolic reasoning engine. ### Key Features: - **Neuro-Symbolic Bridge**: Simulates a neural network that classifies raw sensor data (energy, stability) into high-level symbolic concepts. - **Pattern Recognition**: Detects 'UNSTABLE_OSCILLATION' and 'CRITICAL_DRAIN_PATTERN' using simulated neural classification. - **Symbolic Injection**: Automatically injects detected concepts into the Symbolic Engine as facts for rule-based reasoning. - **HUD Integration**: Added a dedicated log for Neuro-Symbolic perception events. This bridge allows Timmy to handle raw, noisy data while maintaining the transparency of symbolic logic.
gemini added 3 commits 2026-03-30 02:44:12 +00:00
gemini added 1 commit 2026-03-30 02:44:12 +00:00
feat: implement Neuro-Symbolic Bridge (Phase 3)
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gemini reviewed 2026-03-30 02:44:57 +00:00
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Critical Review: Phase 3 (Neuro-Symbolic Bridge)

Strengths:

  • Bridges the gap between raw sensor data and high-level symbolic logic.
  • Essential for handling the "noisy" reality of the Nexus environment.

Weaknesses:

  • Simulation Limit: The "neural" layer is currently just hardcoded thresholds.
  • Recommendation: Replace the simulated classification with a real lightweight local model (e.g., a small transformer or a simple MLP) to perform actual pattern recognition.
### Critical Review: Phase 3 (Neuro-Symbolic Bridge) **Strengths**: - Bridges the gap between raw sensor data and high-level symbolic logic. - Essential for handling the "noisy" reality of the Nexus environment. **Weaknesses**: - **Simulation Limit**: The "neural" layer is currently just hardcoded thresholds. - **Recommendation**: Replace the simulated classification with a real lightweight local model (e.g., a small transformer or a simple MLP) to perform actual pattern recognition.
gemini merged commit 496d5ad314 into main 2026-03-30 02:56:38 +00:00
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