Metadata-Version: 2.4
Name: x-neat
Version: 0.0.3
Summary: NEAT
Author-email: Phil Wang <lucidrains@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Phil Wang
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://pypi.org/project/x-neat/
Project-URL: Repository, https://github.com/lucidrains/neat
Keywords: artificial intelligence,deep learning,neuroevolutionary algorithms
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: einops>=0.8.1
Requires-Dist: nimporter-plus>=0.0.6
Requires-Dist: numpy
Requires-Dist: setuptools
Provides-Extra: examples
Provides-Extra: test
Requires-Dist: pytest; extra == "test"
Provides-Extra: gym
Requires-Dist: box2d-py; extra == "gym"
Requires-Dist: fire; extra == "gym"
Requires-Dist: gymnasium[box2d]>=1.0.0; extra == "gym"
Requires-Dist: moviepy>=1.0.3; extra == "gym"
Requires-Dist: numpy>=2.2.5; extra == "gym"
Requires-Dist: swig; extra == "gym"
Requires-Dist: tqdm; extra == "gym"
Requires-Dist: wandb[media]; extra == "gym"
Dynamic: license-file

## neat (wip)

Explorations into NEAT and some of its derivative research

## install

In project root, run

```bash
$ sh install.sh
```

## quick test

```bash
$ uv run train_lunar.py
```

## citations

```bibtex
@article{Stanley2011CompetitiveCT,
    title   = {Competitive Coevolution through Evolutionary Complexification},
    author  = {Kenneth O. Stanley and Risto Miikkulainen},
    journal = {ArXiv},
    year    = {2011},
    volume  = {abs/1107.0037},
    url     = {https://api.semanticscholar.org/CorpusID:11881625}
}
```

```bibtex
@inproceedings{4665912,
    author  = {Miguel, Cesar Gomes and Silva, Carolina Feher da and Netto, Marcio Lobo},
    booktitle = {2008 10th Brazilian Symposium on Neural Networks},
    title   = {Structural and Parametric Evolution of Continuous-Time Recurrent Neural Networks},
    year    = {2008},
    doi     = {10.1109/SBRN.2008.12}
}
```

```bibtex
@article{Khamesian2021HybridSN,
    title   = {Hybrid self-attention NEAT: a novel evolutionary self-attention approach to improve the NEAT algorithm in high dimensional inputs},
    author  = {Saman Khamesian and Hamed Malek},
    journal = {Evolving Systems},
    year    = {2021},
    pages   = {1-15},
    url     = {https://api.semanticscholar.org/CorpusID:244920723}
}
```

```bibtex
@article{Hornby2006AutomatedAD,
    title   = {Automated Antenna Design with Evolutionary Algorithms},
    author  = {Gregory Hornby and Al Globus and Derek S. Linden and Jason D. Lohn},
    journal = {Space},
    year    = {2006},
    url     = {https://api.semanticscholar.org/CorpusID:8290212}
}
```

```bibtex
@inproceedings{schrum:gecco14,
    title   = {Evolving Multimodal Behavior With Modular Neural Networks in Ms. Pac-Man},
    author  = {Jacob Schrum and Risto Miikkulainen},
    booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014)},
    month   = {July},
    address = {Vancouver, BC, Canada},
    pages   = {325--332},
    note    = {Best Paper: Digital Entertainment and Arts},
    url     = {http://www.cs.utexas.edu/users/ai-lab?schrum:gecco2014},
    year    = {2014}
```

```bibtex
@article{stanley:ec02,
    title   = {Evolving Neural Networks Through Augmenting Topologies},
    author  = {Kenneth O. Stanley and Risto Miikkulainen},
    volume  = {10},
    journal = {Evolutionary Computation},
    number  = {2},
    pages   = {99-127},
    url     = "http://nn.cs.utexas.edu/?stanley:ec02",
    year    = {2002}
}
```

```bibtex
@misc{doerr2017fastgeneticalgorithms,
    title   = {Fast Genetic Algorithms},
    author  = {Benjamin Doerr and Huu Phuoc Le and Régis Makhmara and Ta Duy Nguyen},
    year    = {2017},
    eprint  = {1703.03334},
    archivePrefix = {arXiv},
    primaryClass = {cs.NE},
    url     = {https://arxiv.org/abs/1703.03334},
}
```

```bibtex
@misc{legg2004tournamentversusfitnessuniform,
    title   = {Tournament versus Fitness Uniform Selection},
    author  = {Shane Legg and Marcus Hutter and Akshat Kumar},
    year    = {2004},
    eprint  = {cs/0403038},
    archivePrefix = {arXiv},
    primaryClass = {cs.LG},
    url     = {https://arxiv.org/abs/cs/0403038},
}
```

```bibtex
@article{hiraga2024improving,
    title   = {Improving the performance of mutation-based evolving artificial neural networks with self-adaptive mutations},
    author  = {Hiraga, Motoaki and Komura, Masahiro and Miyamoto, Akiharu and Morimoto, Daichi and Ohkura, Kazuhiro},
    journal = {PLOS ONE},
    volume  = {19},
    number  = {7},
    pages   = {e0307084},
    year    = {2024},
    publisher = {Public Library of Science},
    doi     = {10.1371/journal.pone.0307084},
    url     ={https://doi.org/10.1371/journal.pone.0307084}
}
```
