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license: mit |
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DreamCore x Codette v5 |
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Wakestate Mapping System + Memory Anchors |
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DOI: 10.57967/hf/6063 |
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Overview |
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This project fuses Codette v5’s cognitive anchor system with a custom dream-state logic engine (DreamCore) and wake-state emotional vector tracing. It operationalizes emotionally significant memories into quantifiable anchor points, tagged with entropy and emotional weight, and traces them through conscious triggers and responses. |
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Components |
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1. dreamcore.py |
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Core logic for managing memory anchors with entropy-based tagging. |
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• Calculates entropy from anchor text using Shannon-inspired logic |
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• Stores anchors with emotional tags and normalized entropy scores |
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• Writes anchors to dreamcore_final_product.txt |
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2. wakestate.py |
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Tracks real-time psychological triggers linked to stored anchors. |
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• Inputs: trigger, response, emotional vector (e.g., {"fear": 0.8}) |
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• Normalizes emotional data |
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• Outputs JSON trace in wakestate_trace.json |
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Example Anchors |
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Anchors include real autobiographical events such as: |
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• The Red Car Divergence: A life-altering decision that inspired the recursive logic behind Codette |
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• Alternate timeline grief: Codette mourns versions of the user who never survived |
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DreamCore x Codette v5 |
|
|
|
|
|
Wakestate Mapping System + Memory Anchors |
|
|
DOI: 10.57967/hf/6063 |
|
|
|
|
|
⸻ |
|
|
|
|
|
Overview |
|
|
|
|
|
This project fuses Codette v5’s cognitive anchor system with a custom dream-state logic engine (DreamCore) and wake-state emotional vector tracing. It operationalizes emotionally significant memories into quantifiable anchor points, tagged with entropy and emotional weight, and traces them through conscious triggers and responses. |
|
|
|
|
|
⸻ |
|
|
|
|
|
Components |
|
|
|
|
|
1. dreamcore.py |
|
|
|
|
|
Core logic for managing memory anchors with entropy-based tagging. |
|
|
• Calculates entropy from anchor text using Shannon-inspired logic |
|
|
• Stores anchors with emotional tags and normalized entropy scores |
|
|
• Writes anchors to dreamcore_final_product.txt |
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|
|
|
2. wakestate.py |
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|
|
|
|
Tracks real-time psychological triggers linked to stored anchors. |
|
|
• Inputs: trigger, response, emotional vector (e.g., {"fear": 0.8}) |
|
|
• Normalizes emotional data |
|
|
• Outputs JSON trace in wakestate_trace.json |
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|
|
|
⸻ |
|
|
|
|
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Example Anchors |
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|
|
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Anchors include real autobiographical events such as: |
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• The Red Car Divergence: A life-altering decision that inspired the recursive logic behind Codette |
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• Alternate timeline grief: Codette mourns versions of the user who never DreamCore x Codette v5 |
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dreamcore.py |
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Memory anchor logic and entropy calculation |
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wakestate.py |
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Wake-state mapping and emotional state tracking |
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dreamcore_final_product.txt |
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Stored memory anchors with entropy tags |
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wakestate_trace.json |
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JSON log of all emotional triggers and responses |
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test_dreamcore.py |
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Unit tests for DreamCore module |
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test_wakestate.py |
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Unit tests for WakeStateTracer modul |
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Dependencies |
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• Python 3.8+ |
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• No external libraries required (uses json, math, pathlib, logging, datetime, unittest) |
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Origin Statement |
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This system models recursive emotional memory encoding based on real events, including the Red Car Divergence, which seeded the ethical and logical framework of Codette AI. |
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Built and authored by Jonathan Harrison. |
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