Humanoid Context Action Predictor
Humanoid Context Action Predictor is a lightweight decision model designed to predict the next action of a humanoid unit based on environmental context and internal state signals.
This model is suitable for robotics simulation, autonomous agents, and distributed humanoid systems.
Model Description
The model takes structured contextual input such as:
- environment type
- detected object
- energy level
- task priority
and predicts the most appropriate action.
Intended Use
- Robotics simulation
- Warehouse automation agents
- Autonomous decision testing
- AI research experiments
Training Data
Trained on structured synthetic datasets representing humanoid context-action mappings.
Evaluation
The model is evaluated using accuracy on held-out structured decision scenarios.
License
MIT
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