Tensorized NeuroEvolution of Augmenting Topologies for GPU Acceleration

Author:

Wang Lishuang1ORCID,Zhao Mengfei1ORCID,Liu Enyu1ORCID,Sun Kebin1ORCID,Cheng Ran1ORCID

Affiliation:

1. Southern University of Science and Technology, Shenzhen, China

Publisher

ACM

Reference33 articles.

1. Martín Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Rafal Jozefowicz Yangqing Jia Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dan Mané Mike Schuster Rajat Monga Sherry Moore Derek Murray Chris Olah Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Viégas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2015. TensorFlow Large-scale machine learning on heterogeneous systems. 10.5281/zenodo.4724125

2. Joshua E. Auerbach and Josh C. Bongard. 2011. Evolving complete robots with CPPN-NEAT: The utility of recurrent connections. In Proceedings of the Annual Conference on Genetic and Evolutionary Computation. 1475--1482.

3. b2developer. 2022. MonopolyNEAT: NEAT implemented into Monopoly with a knockout tournament scheme. https://github.com/b2developer/MonopolyNEAT Accessed: 2023-08-15.

4. Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang and Wojciech Zaremba. 2016. OpenAI Gym. arXiv:1606.01540

5. Language models are few-shot learners;Brown Tom;Advances in Neural Information Processing Systems,2020

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