decijax
decijax is an early-stage library which aims to provide algorithms for a
variety of sequential decision-making problems. It currently provides implementations
of several acquisition functions for Bayesian optimisation, including
probability of improvement, expected improvement and Thompson sampling. The
implementations are built upon the JAX library, enabling automatic differentiation,
vectorisation, and just-in-time (JIT) compilation for high performance. This allows for efficient research, development, and deployment of decision-making agents.
⚠️ Warning
decijaxis currently under active development, and the API is likely to change in the near future.
Table of Contents
Installation
decijax requires Python 3.11 or later. Install the latest release from PyPI with:
pip install decijax
Documentation
Available at https://thomas-christie.github.io/decijax/.
Contributing
Please refer to the contributing guidelines file for guidelines on how to contribute to the project.
License
decijax is distributed under the terms of the MIT license.
1 maintainer
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