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

python

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