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This project provides GOLang implementation of Neuro-Evolution of Augmenting Topologies (NEAT) with Novelty Search optimization aimed to solve deceptive tasks with strong local optima

License: MIT License

Go 83.81% Python 11.24% Makefile 4.95%
artificial-neural-networks augmenting-topologies explainable-ai explainable-artificial-intelligence golang modular-ai neat neuroevolution novelty-search reinforcement-learning-algorithms unsupervised-learning unsupervised-learning-algorithms unsupervised-machine-learning

goneat_ns's Introduction

Iaroslav Omelianenko's GitHub stats Top Langs

πŸ“– My Books

πŸ“‘ My Papers

  • Omelianenko, Iaroslav. Applying Deep Machine Learning for Psycho-Demographic Profiling of Internet Users Using O.C.E.A.N. Model of Personality. arXiv [Cs.LG], 2017. P. 1–24. DOI: https://doi.org/10.48550/arxiv.1703.06914.
  • Omelianenko, Iaroslav. Applying Advanced Machine Learning Models to Classify Electro-Physiological Activity of Human Brain for Use in Biometric Identification. arXiv [Cs.LG], 2017. P. 1–8. DOI: 10.48550/arxiv.1708.01167
  • Omelianenko, I. Creation of Autonomous Artificial Intelligent Agents using Novelty Search method of fitness function optimization. Hal.science, 2018. P. 1–7. URL: https://hal.science/hal-01868756
  • Omelianeko, I. Artificial Swarm Intelligence and Cooperative Robotic Systems. Preprints.org, 2019, P. 1–8. DOI: 10.20944/preprints201901.0282.v1
  • Omelianeko, I. Simulation of the autonomous maze navigation using the NEAT algorithm. Problems in programming, 2023. Vol. 4, P. 76–89. DOI: 10.15407/pp2023.04.076
  • Omelianenko, I. and Sinitsyn, I. Artificial swarm intelligence. International Scientific Technical Journal "Problems of Control and Informatics", 2024, Vol. 69. N 3. P. 91–103. DOI: 10.34229/1028-0979-2024-3-7

πŸ”­ Researcher Profiles

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