BCLA Simulation Toolkit - Functional Requirements Document
1. Executive Summary
The Binary Coded Layered Autonoma (BCLA) Simulation Toolkit is a research platform for studying emergent computational phenomena arising from the interaction between autonomous agents and constrained cellular automata. The toolkit must support large-scale simulations (up to 2000×2000 grids), provide sophisticated analysis tools for capturing rare events, and enable rigorous experimental measurement of local dynamics and wave propagation behaviors.
2. System Architecture Overview
2.1 Multi-Layer Computational Model
- Agent Layer: CPU-based autonomous agents representing growth cones
- Substrate Layer: GPU-accelerated grid representing environmental state
- Life Layer: WebGPU-based Conway’s Game of Life evolution constrained by substrate
2.2 Performance Requirements
- Grid Size: Support up to 2000×2000 cells minimum
- Frame Rate: Maintain 30+ FPS for real-time interaction
- Agent Count: Support 1-32 simultaneous agents
- Substrate Colors: 2-8 distinct substrate states
- Memory Efficiency: Logarithmic backup storage for extended simulation history
3. Core Simulation Engine
3.1 Agent System (CPU)
Functional Requirements:
- Multi-agent support with independent or coordinated behavior patterns
- Binary-encoded movement rules with configurable rule vectors
- Multi-sensor extensions supporting 2-4 environmental inputs
- Substrate modification capabilities with configurable marking patterns
- Collision detection and interaction between agents
- Support for complementary agent populations with opposing behaviors
Technical Specifications:
- Agent state: position (x,y), direction, rule vector R[], activation vector A[]
- Movement algorithm: sense → decide → modify → move
- Sensor modes: current color only, current + ahead, current + lateral
- Memory-free reactive behavior (Markovian dynamics)
3.2 Life Evolution Engine (WebGPU)
Functional Requirements:
- Conway’s Game of Life rules implemented as compute shaders
- Substrate-constrained evolution (Life only on marked cells)
- Efficient neighbor calculation for sparse substrates
- Double-buffered state management for stable evolution
- Configurable boundary conditions (wrap-around, fixed borders)
Technical Specifications:
- WebGPU compute shader implementation
- Texture-based or compute buffer storage
- Parallel processing across entire grid
- Integration with substrate modification events
3.3 Substrate Management
Functional Requirements:
- Multi-color substrate state tracking
- Efficient CPU→GPU data transfer for agent modifications
- Sparse representation optimization for mostly-empty grids
- Real-time substrate state queries for agent sensors
4. Temporal Management and History System
4.1 Logarithmic Decimation Backup
Functional Requirements:
- Automatic checkpoint creation with logarithmic time intervals
- Complete system state preservation (agents + substrate + Life patterns)
- Memory-bounded storage with configurable retention policies
- Fast state restoration for any preserved checkpoint
Technical Specifications:
- Checkpoint intervals: every step (last 10), every 10 steps (10-100), every 100 steps (100-1000), etc.
- Compressed state storage for memory efficiency
- Maximum checkpoint count: ~50-100 total checkpoints
- State serialization format supporting all system components
4.2 Playback and Navigation
Functional Requirements:
- Bidirectional simulation (forward/backward stepping)
- Variable speed playback (0.1x to 10x real-time)
- Jump-to-checkpoint navigation
- Branch simulation from any historical state
5. Analysis and Measurement Tools
5.1 Regional Selection and Control
Functional Requirements:
- Window/rectangle selection tool for isolating regions of interest
- Brush-based arbitrary region selection
- Multiple simultaneous region tracking
- Region-specific state modification and control
Capabilities:
- Trail segment isolation and analysis
- Chaotic nucleus boundary definition
- Signal injection zones
- Measurement area designation
5.2 Signal Analysis Mode
Functional Requirements:
- Controlled pattern injection at specified coordinates
- Noise generation with configurable distributions (uniform, Gaussian, custom)
- State filling operations (specific colors, Life patterns)
- Multi-point synchronized perturbations
- Before/after comparison tools
5.3 Local Dynamics Measurement
Functional Requirements:
- Trail Conductivity Analysis:
- Signal attenuation measurement along pathways
- Pattern preservation distance tracking
- Propagation velocity profiling
- Directional bias detection
- Edge effect characterization
- Chaotic Nucleus Characterization:
- Pattern complexity metrics (entropy, period detection)
- Input/output transformation analysis
- Stability and perturbation recovery measurement
- Activity level quantification
- Wave Propagation Studies:
- Multi-signal interference analysis
- Reflection/transmission at trail junctions
- Boundary condition effects
- Signal merging/splitting behavior
5.4 Rare Event Detection
Functional Requirements:
- Automated pattern recognition for oscillatory agent pairs
- Anomaly detection for unusual behaviors
- Event flagging and automatic checkpoint creation
- Statistical behavior tracking across multiple simulation runs
6. User Interface Requirements
6.1 Real-Time Visualization
Functional Requirements:
- Multi-layer rendering with configurable opacity/visibility
- Zoom and pan capabilities for detailed inspection
- Real-time performance metrics display
- Color-coded visualization for different substrate states and Life patterns
6.2 Control Interface
Functional Requirements:
- Parameter adjustment controls (agent rules, substrate colors, etc.)
- Simulation speed controls (pause, step, variable speed)
- Checkpoint management interface
- Region selection and analysis tools
- Export functionality for data and visualizations
6.3 Experimental Design Interface
Functional Requirements:
- Parameter sweep configuration
- Batch simulation management
- Experimental protocol scripting
- Results comparison and analysis tools
7. Data Export and Analysis
7.1 Data Export Formats
Requirements:
- System state snapshots (complete simulation state)
- Measurement data (CSV, JSON formats)
- Visualization exports (images, videos, interactive demos)
- Statistical analysis data for external processing
7.2 Integration Capabilities
Requirements:
- API for external analysis tools
- Scripting interface for automated experiments
- Integration with statistical analysis software
- Reproducible experiment configuration management
8. Performance and Scalability
8.1 Computational Performance
- Target Grid Size: 2000×2000 cells minimum
- Frame Rate: 30+ FPS for interactive use
- Memory Usage: Efficient sparse storage for large, mostly-empty grids
- Scalability: Linear performance scaling with active cell count
8.2 Storage Requirements
- Checkpoint Storage: Logarithmic growth, ~1GB max for extended sessions
- Export Data: Configurable compression and storage optimization
- Temporary Files: Automatic cleanup and management
9. Research-Specific Features
9.1 Complementary Agent Dynamics
Requirements:
- Support for particle/antiparticle agent pairs
- Interface dynamics analysis between opposing populations
- Spatial control mechanisms using complementary rules
- Oscillatory pair detection and characterization
9.2 Multi-Timescale Analysis
Requirements:
- Simultaneous measurement of fast (Life) and slow (agent) dynamics
- Temporal correlation analysis tools
- Quasi-static state detection and characterization
- Transition event identification and analysis
9.3 Experimental Reproducibility
Requirements:
- Complete parameter state preservation
- Random seed management for reproducible results
- Experiment configuration templates
- Version control integration for research documentation
10. Technical Architecture
10.1 Technology Stack
- Frontend: Modern web browser with WebGPU support
- Compute Engine: WebGPU for Life evolution, JavaScript for agents
- Storage: IndexedDB for checkpoint persistence
- Visualization: Canvas 2D/WebGL for rendering
- Analysis: Web Workers for background computation
10.2 Platform Requirements
- Browser Support: Chrome/Edge with WebGPU enabled
- Hardware: Discrete GPU recommended for large grid sizes
- Memory: 8GB RAM minimum for 2000×2000 simulations
- Storage: 2GB available space for checkpoint history
11. Validation and Testing
11.1 Correctness Validation
- Conway’s Life rule verification against reference implementations
- Agent behavior validation against specification
- Checkpoint/restore integrity testing
- Cross-platform consistency verification
11.2 Performance Testing
- Large grid performance benchmarking
- Memory usage profiling and optimization
- Long-running simulation stability testing
- Checkpoint system performance validation
12. Future Extensibility
12.1 Planned Extensions
- Additional cellular automata rules beyond Conway’s Life
- Advanced agent AI using reinforcement learning
- 3D simulation capabilities
- Distributed simulation across multiple GPUs
12.2 API Design
- Modular architecture supporting plugin development
- Extensible measurement framework
- Configurable visualization pipeline
- External tool integration capabilities
This functional requirements document serves as the foundation for implementing a comprehensive research platform capable of discovering, analyzing, and documenting the novel computational phenomena exhibited by BCLA systems.