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

Physical Symbolic Optimization (Φ-SO) Screenshot 1

Project Activity

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Categories

Physics, Machine Learning, Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning Algorithms

License

MIT License

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Physics Software, Python Machine Learning Software, Python Reinforcement Learning Frameworks, Python Reinforcement Learning Libraries, Python Reinforcement Learning Algorithms

Registered

2024-08-14
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