Human-like physical understanding through qualitative relationships and causal reasoning
Project description
💰 Support This Research - Please Donate!
🙏 If this library helps your research or project, please consider donating to support continued development:
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Qualitative Reasoning
🤔 Commonsense physics simulation
Forbus, K. D. (1984) - "Qualitative process theory"
📦 Installation
pip install qualitative-reasoning
🚀 Quick Start
import qualitative_reasoning
import numpy as np
# Create qualitative reasoner
reasoner = qualitative_reasoning.QualitativeReasoner()
# Define qualitative variables
temperature = qualitative_reasoning.QualitativeQuantity(
'temperature',
['cold', 'warm', 'hot']
)
pressure = qualitative_reasoning.QualitativeQuantity(
'pressure',
['low', 'medium', 'high']
)
# Create qualitative state
state = qualitative_reasoning.QualitativeState({
'temperature': 'warm',
'pressure': 'medium'
})
# Perform envisionment
env = qualitative_reasoning.QualitativeEnvisionment(reasoner)
transitions = env.generate_transitions(state)
print(f"✅ Possible transitions: {len(transitions)}")
for transition in transitions:
print(f" → {transition}")
🎓 About the Implementation
Implemented by Benedict Chen - bringing foundational AI research to modern Python.
📧 Contact: benedict@benedictchen.com
📖 Citation
If you use this implementation in your research, please cite the original paper:
Forbus, K. D. (1984) - "Qualitative process theory"
📜 License
Custom Non-Commercial License with Donation Requirements - See LICENSE file for details.
💰 Support This Work - Donation Appreciated!
This implementation represents hundreds of hours of research and development. If you find it valuable, please consider donating:
💳 DONATE VIA PAYPAL - CLICK HERE
Your support helps maintain and expand these research implementations! 🙏
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