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## Synopsis

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**Alnos** is an implementation of an
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adaptation of
[L*](http://www.cs.berkeley.edu/~dawnsong/teaching/s10/papers/angluin87.pdf) to
nondeterministic systems. The code is based on these scientific papers:
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* [`[1]` Active Learning of Nondeterminisitc Systems from an ioco Perspective](http://link.springer.com/chapter/10.1007%2F978-3-662-45234-9_16)
* [`[2]` Approximate Active Learning of Nondeterministic Input Output Transition Systems](http://www.italia.cs.ru.nl/html/papers/VT15.pdf)
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The goal is to construct a model of a system for model-based testing,
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simulation, or model checking.

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### Python version

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The project is coded in Python3 and tested using Python3.4.
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## Included Libraries

[NumPy](https://github.com/numpy/numpy)

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## Code Example

Check [the examples folder](examples/) for how to use it.

## Motivation

This code exists as a support implementation to the papers mentioned previously.

## Installation

Clone the repository. Then you can modify any file in [examples](examples/),
or create your own.
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[Tic Tac Toe](examples/tictactoe/) uses a real *black box* system under learning.
There is also an example for learning a model of it using another learning
tool: [LearnLib](https://github.com/LearnLib/learnlib).
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## Contributors

If you want to contribute, or if you have questions, you can contact me by
checking [my contact details](https://gitlab.science.ru.nl/u/mvolpato).

## License

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[This license](./LICENSE) applies to most of the files. Some files may have a different license. If so, the license can be found at the top of the source code.
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If no license is found at the top of the source, [this license](./LICENSE) is applied.