Mojana COMET - Active Inference + Stackelberg Game Theory
Fine-tuned COMET model with Active Inference and Stackelberg Game Theory reasoning for robotics applications.
Model Description
Based on Flan-T5-base (247M parameters), extended with:
- Active Inference: xStateSpace, xPriorBeliefs, xEFEAnalysis, xSelectedAction, etc.
- Stackelberg Game Theory: xGameAgents, xStackelbergEquilibrium, xCommitmentValue, etc.
- Commonsense: ATOMIC relations (xWant, xNeed, xEffect, xIntent)
- Physical Reasoning: PIQA (xPhysicalSolution)
Training Data
- Active Inference examples: 1.87M
- Stackelberg examples: 580K
- PIQA: 2M
- ATOMIC: 957K
- Custom heuristics: 495K
Usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("Haya-as/mojana-comet-unified")
tokenizer = AutoTokenizer.from_pretrained("Haya-as/mojana-comet-unified")
# Active Inference query
prompt = "The robot detects smoke in the kitchen [xEFEAnalysis]"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Relations
| Type | Relations |
|---|---|
| Active Inference | xStateSpace, xPriorBeliefs, xPriorEntropy, xGoalState, xActionSpace, xEFEAnalysis, xSelectedAction, xBeliefUpdateProcess |
| Stackelberg | xGameAgents, xLeaderStrategies, xFollowerStrategies, xPayoffStructure, xFollowerBestResponses, xLeaderOptimization, xStackelbergEquilibrium, xCommitmentValue |
| ATOMIC | xWant, xNeed, xEffect, xIntent, xAttr, HinderedBy, ObjectUse |
| Physical | xPhysicalSolution, xPhysicalAlternative |
License
MIT
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