Cognitive Decision Engine v1
Overview
Model ini bertugas menentukan aksi terbaik berdasarkan kondisi lingkungan dan status internal humanoid.
Dirancang untuk:
- Real-time decision making
- Safety-first control system
- Mission-aware navigation
Problem Type
Multiclass Classification (4 classes)
Input Features
- obstacle_proximity_cm
- human_presence_confidence
- battery_level_percent
- mission_priority_level
- internal_temperature_celsius
- system_latency_ms
- environmental_risk_index
Output
- decision_action:
- proceed
- slow_down
- stop
- emergency_shutdown
Architecture
- Input Normalization
- Dense(256) + ReLU
- BatchNormalization
- Dense(128) + ReLU
- Dropout(0.35)
- Dense(64) + ReLU
- Dense(4) + Softmax
Loss Function
Categorical Crossentropy
Optimizer
Adam (learning_rate=0.0007)
Metrics
- Accuracy
- Precision (Macro)
- Recall (Macro)
- F1 Score (Macro)
Training Strategy
- 80/20 Train-Test Split
- Stratified Sampling
- Early Stopping (patience=12)
Expected Performance (Simulated)
- Accuracy: 92–95%
- F1 Macro: ~0.91
Deployment Scenario
- Autonomous navigation core
- Safety override system
- Human-aware robotic interaction
Version
v1 – Production-ready baseline