hyperc-ai/ordered
Entropy-controlled contexts in Python
This project helps operations engineers, manufacturers, and automated system designers create reliable, deterministic workflows in Python that achieve a specific goal. You define your system's initial state, the possible actions it can take, and the desired outcome. The tool then guarantees the system will reach that outcome without errors, identifying the optimal sequence of actions.
No commits in the last 6 months. Available on PyPI.
Use this if you need to ensure a sequence of operations always reaches a specific target state without errors or unpredictable outcomes, especially in automated decision-making or control systems.
Not ideal if your Python code involves extensive file I/O, complex list manipulations, or standard `for` loops within the critical decision-making parts, as these are not fully supported.
Stars
39
Forks
3
Language
Python
License
MIT
Category
Last pushed
Oct 29, 2021
Commits (30d)
0
Dependencies
3
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