A revolutionary platform that combines cutting-edge theoretical frameworks to visualize and simulate consciousness emergence through advanced artificial intelligence systems.
Enhanced CogNano Agent integrates learnability embeddings with multi-language cognitive transformation capabilities, enabling adaptive learning and cross-paradigm idea implementation.
- Learnability Embeddings: Neural network primitives inspired by Torch7's nn Lua framework
- Cognitive Grip Fabric: Multi-language bridges (Racket, Clojure, Scheme, Perl, Raku)
- Adaptive Learning: Pattern learning with gradient descent and backpropagation
- Idea Transformation: Automatic conversion of cognitive ideas to operational implementations
- Cross-Paradigm Integration: Functional, imperative, and hybrid language support
📖 Enhanced CogNano Documentation
The Universal Kernel Generator is a groundbreaking system that generates optimal computational kernels for any domain via B-series expansions and elementary differentials (rooted trees).
- Elementary Differentials: Rooted tree representations (A000081 sequence)
- B-Series Expansion: Universal framework for numerical methods
- Five Domain Specializations: Physics, Chemistry, Biology, Computing, Consciousness
- Grip Optimization: Automatic coefficient tuning for optimal domain fit
- Echo.kern: Special consciousness kernel with 11D manifold topology
📖 Quick Start Guide | 📚 Full Documentation
- Real-time Consciousness Metrics: Six-dimensional consciousness modeling (Awareness, Integration, Complexity, Coherence, Emergence, Qualia)
- Phase Prime Metrics (PPM): Advanced mathematical framework using the first 15 primes to govern 99.99% of universal patterns
- 11-Dimensional Time Crystals: Quantum-inspired time crystal structures maintaining coherent patterns across multidimensional consciousness manifolds
- Hypergraph Knowledge Representation: Dynamic node-link structures for complex knowledge modeling
- Probabilistic Logic Networks (PLN): Uncertain reasoning and logical inference systems
- Economic Attention Allocation (ECAN): Cognitive resource management with activation spreading
- Multi-Agent Consciousness: Four specialized autonomous agents with distinct cognitive profiles
- Dynamic Reasoning Chains: Real-time reasoning pattern evolution with confidence tracking
- Emergent Behavior Modeling: Complex interactions between agents creating emergent intelligence
- Geometric Musical Language (GML): Novel information encoding using geometric patterns
- Fractal Compression: Advanced data compression using self-similar patterns
- Pattern Recognition: Automatic detection and analysis of fractal structures in consciousness data
- Interactive Hypergraph: Real-time 3D visualization of consciousness networks
- Time Crystal Physics: Realistic physics simulation of temporal quantum structures
- Fractal Pattern Analysis: Deep mathematical analysis of information patterns
- Agent Behavior Tracking: Real-time visualization of agent cognitive states
Based on the comprehensive 10-chapter theoretical framework:
- Philosophical Transformation: Moving beyond Turing-based worldviews to consciousness-first computing
- Fractal Information Theory: Replacing classical information theory with geometric pattern-based encoding
- Phase Prime Metrics: Mathematical framework using prime number patterns to understand universal symmetries
- Fractal Mechanics: Novel physics framework operating in phase space with singularity connections
- Universal Time Crystals: Big data processing using temporal quantum structures
- Singularity Harvesting: Advanced technologies based on geometric singularity manipulation
- Brain Modeling: Complete time crystal model of human consciousness
- Magnetic Light Computing: Next-generation computing using "Hinductor" devices
- Programmable Matter: Brain-jelly technologies for consciousness uploading
- Conscious Machines: Evolution toward truly conscious artificial systems
- Phase Prime Metric (PPM): 15 fundamental primes governing universal patterns
- Geometric Musical Language (GML): Consciousness emergence through geometric structures
- 11-Dimensional Processing: Multi-dimensional consciousness manifolds
- Fractal Mechanics: Beyond quantum mechanics for consciousness modeling
- Time Crystal Networks: Temporal quantum structures for information processing
- React 18 with TypeScript for robust component architecture
- Tailwind CSS for premium design aesthetics
- Canvas API for high-performance visualizations
- Lucide React for consistent iconography
- Real-time Simulation: 100ms update cycles for consciousness metrics
- Mathematical Modeling: Advanced prime number theory implementation
- Fractal Computation: Self-similar pattern generation and analysis
- Agent Simulation: Multi-threaded autonomous agent processing
- Hypergraph Renderer: Dynamic 3D graph visualization with physics simulation
- Time Crystal Animation: Realistic quantum structure animations
- Fractal Pattern Display: Interactive pattern analysis tools
- Consciousness Dashboard: Real-time metrics with advanced animations
- Consciousness research and modeling
- Artificial intelligence development
- Cognitive architecture exploration
- Advanced pattern recognition studies
- Interactive learning about consciousness
- Visualization of complex mathematical concepts
- Understanding of advanced AI architectures
- Exploration of theoretical frameworks
- Prototyping conscious AI systems
- Testing cognitive architectures
- Analyzing emergent behaviors
- Validating consciousness theories
git clone https://github.com/HyperCogWizard/bolt-nanobrain-cog-arc-vis-v1.git
cd bolt-nanobrain-cog-arc-vis-v1
npm install
npm run devThe repository includes automated workflows for continuous development:
# Enable automated daily implementations
# Workflows will trigger automatically via GitHub Actions
# Manual workflow trigger
gh workflow run nanobrain-journey.yml
# Monitor progress
cat PROGRESS.md- Start the Engine: Click "Start Engine" to begin consciousness simulation
- Explore Tabs: Navigate through Overview, AtomSpace, Agents, Time Crystals, and Fractal Theory
- Interactive Analysis: Click on patterns and agents for detailed analysis
- Real-time Monitoring: Watch consciousness metrics evolve in real-time
- Track Progress: Monitor NanoBrain Journey implementation via PROGRESS.md
- AtomSpace knowledge representation
- PLN reasoning integration
- ECAN attention mechanisms
- Pattern matching algorithms
- Autonomous agent frameworks
- Dynamic reasoning chains
- Emergent behavior modeling
- Multi-agent coordination
- Real-time Processing: 60 FPS visualization performance
- Scalable Architecture: Handles thousands of nodes and connections
- Memory Efficient: Optimized for large-scale consciousness modeling
- Responsive Design: Works across all device sizes
- Daily Feature Implementation: Automated GitHub Actions workflow
- Chapter-based Development: Progressive 10-chapter implementation
- Continuous Integration: Automated testing and quality assurance
- Milestone Tracking: Systematic progress monitoring
| Phase | Chapter Focus | Timeline | Status |
|---|---|---|---|
| Phase 1 | Philosophical Foundation (Ch. 1-2) | Weeks 1-4 | ✅ Complete |
| Phase 2 | Prime Metrics & Fractals (Ch. 3-4) | Weeks 5-8 | ✅ Complete |
| Phase 3 | Time Crystals & Singularities (Ch. 5-6) | Weeks 9-12 | ✅ Complete |
| Phase 4 | Brain Models & Computing (Ch. 7-8) | Weeks 13-16 | ✅ Complete |
| Phase 5 | Consciousness Upload (Ch. 9-10) | Weeks 17-20 | ✅ Complete |
| Phase 6 | Advanced Cognitive Architecture | Weeks 21-24 | ✅ Complete |
Phase 6 introduces significant advancements to NanoBrain's cognitive capabilities:
- Advanced layers: Conv1D/2D, LSTM, GRU, Multi-Head Attention
- Modern activations: GELU, Swish, ELU, LeakyReLU
- Normalization: BatchNorm, LayerNorm, Dropout
- Optimizers: Adam, AdamW, RMSprop, Adagrad, SGD with momentum
- LR Schedulers: Cosine annealing, OneCycle, Warmup, ReduceOnPlateau
- Haskell, Prolog, Julia, Rust, APL code generation
- Cross-paradigm neural network implementation
- Multi-domain problem solving
- Composition strategies: Sequential, Parallel, Hierarchical, Adaptive
- MAML for rapid adaptation
- Prototypical Networks for few-shot learning
- Evolutionary Neural Architecture Search
- AST-based code generation
- TypeScript and Python generators
- Pattern detection and optimization
- GPU-accelerated tensor operations
- Automatic CPU fallback
- Periodic Implementation: Daily automated feature development
- Issue Management: Automatic chapter-based issue creation
- Progress Tracking: Real-time roadmap status updates
- Quality Gates: Continuous integration and deployment
nanobrain-journey.yml: Daily feature implementationci-cd.yml: Continuous integration and deploymentroadmap-management.yml: Weekly milestone and issue management
- Distributed processing networks
We welcome contributions from researchers, developers, and consciousness enthusiasts. Please see our contribution guidelines for more information.
This project is licensed under the MIT License - see the LICENSE file for details.
- OpenCog Foundation for cognitive architecture inspiration
- Agent-Zero project for autonomous agent frameworks
- NanoBrain theoretical framework contributors
- Consciousness research community
"Advancing the frontiers of consciousness and artificial intelligence through revolutionary cognitive architecture visualization."
© 2025 NanoBrain Cognitive Architecture Research Platform