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Physical Symbolic Optimization (Φ-SO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms.
Features
- Physical units constraints, reducing the search space with dimensional analysis
- Class constraints, searching for a single analytical functional form that accurately fits multiple datasets
- PhySO recovers the equation for a damped harmonic oscillator
- Documentation available
- Examples available
- State-of-the-art performance in the presence of noise
Project Samples
Categories
Physics, Machine Learning, Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning AlgorithmsLicense
MIT LicenseFollow Physical Symbolic Optimization (Φ-SO)
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