Humanoid Distributed Reasoning Depth Optimizer (HDRDO)
HDRDO is a meta-cognitive optimization model
that dynamically adjusts reasoning depth
based on uncertainty, risk exposure,
and mission criticality.
The model prevents overthinking and under-reasoning
in decentralized humanoid systems.
Architecture
- Context Severity Encoder
- Risk & Uncertainty Analyzer
- Adaptive Depth Controller
- Resource-Constrained Optimization Layer
- Decision Efficiency Evaluator
Capabilities
- Optimize reasoning depth in real time
- Balance speed vs. accuracy
- Reduce unnecessary computation
- Increase decision robustness
- Adapt to mission-critical scenarios
Training Data
han-decentralized-cognitive-state-transition-dataset-v1
Output
- Recommended reasoning depth level
- Efficiency gain estimate
- Decision latency prediction
- Robustness score
