$\texttt{immrax}$: A Parallelizable and Differentiable Toolbox for Interval Analysis and Mixed Monotone Reachability in JAX
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| Main Authors: | , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866916230069223424 |
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| author | Harapanahalli, Akash Jafarpour, Saber Coogan, Samuel |
| author_facet | Harapanahalli, Akash Jafarpour, Saber Coogan, Samuel |
| contents | We present an implementation of interval analysis and mixed monotone interval reachability analysis as function transforms in Python, fully composable with the computational framework JAX. The resulting toolbox inherits several key features from JAX, including computational efficiency through Just-In-Time Compilation, GPU acceleration for quick parallelized computations, and Automatic Differentiability. We demonstrate the toolbox's performance on several case studies, including a reachability problem on a vehicle model controlled by a neural network, and a robust closed-loop optimal control problem for a swinging pendulum. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2401_11608 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | $\texttt{immrax}$: A Parallelizable and Differentiable Toolbox for Interval Analysis and Mixed Monotone Reachability in JAX Harapanahalli, Akash Jafarpour, Saber Coogan, Samuel Systems and Control Machine Learning Optimization and Control We present an implementation of interval analysis and mixed monotone interval reachability analysis as function transforms in Python, fully composable with the computational framework JAX. The resulting toolbox inherits several key features from JAX, including computational efficiency through Just-In-Time Compilation, GPU acceleration for quick parallelized computations, and Automatic Differentiability. We demonstrate the toolbox's performance on several case studies, including a reachability problem on a vehicle model controlled by a neural network, and a robust closed-loop optimal control problem for a swinging pendulum. |
| title | $\texttt{immrax}$: A Parallelizable and Differentiable Toolbox for Interval Analysis and Mixed Monotone Reachability in JAX |
| topic | Systems and Control Machine Learning Optimization and Control |
| url | https://arxiv.org/abs/2401.11608 |