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1. Rutkovskaya, D. Neural networks, genetic algorithms and fuzzy systems [ Text] / D. Rutkovskaya, L. Rutkovsky, M. Pilinsky. - M.: Hotline-Telecom, 2006-452c.

2. Classification and forecasting methods. Neural networks. URL: https://www.intuit.ru/studies/professional_skill_improvements/1210/courses/6/lecture/178 (date of request: 12.12.2019).

3. Perceptrons [Electronic resource] // Access mode – https://neuralnet.info/chapter/персептроны/ (accessed: 02.12.2019).

4. Ryszard, T. Introduction to Machine learning using Python. Guide for specialists in working with data [Text] / T. Ryshard, B. Barbara. - M.: Hotline-Telecom, 2017. -546c.

5. Donskikh, A. O. The method of artificial reproduction of data in machine learning problems using nonparametric nuclear estimates of the probability distribution density / A. O. Donskikh, A. A. Sirota // Bulletin of the VSU. Series: System Analysis and Information Technologies. - 2017. - No. 3-pp. 142-155.

6. Filist, S. A. Multilayered morphological operators for segmentation of complex-structured raster semitone images / S. A. Filist, A. R. Dabagov, R. A. Tomakova, D. S. Kondrashov/ / Proceedins of the State University. Series: Management, computer engineering, computer science. Medical instrumentation. 2019. Vol. 9. No. 3(32). pp. 44-63.

7. Tomakova, R. A. Mathematical support for recognition and classification of complexly structured biological objects/R. A. Tomakova, A. A. Naser, O. V. Shatalova//International Journal of Applied and Functional Research. - 2012. - No. 4. - p. 48-49.

8. Filist, S. A. Cellular processors in classifiers of multichannel images / S. A. Filist, R. A. Tomakova, A. N. Brezhneva, I. A. Malyutina, V. A. Alekseev// Radio industry. 2019, №1. P. 45-52.

9. Tomakova, R. A. Universal network structures in problems of classification of multidimensional data /R. A. Tomakova, A. A. Naser, O. V. Shatalova, E. V. Rudakova// Modern high-tech technologies. 2012. No. 8. P. 48-49.

10. Rashid, T. Creating a neural network [Text] / T. Rashid. - M.: Publishing House «Williams», 2018. - 435c.

11. Kan, K. A. Neural networks. Evolution [Text] / K. A. Kan. - M.: LitRes, 2019-428c.

12. Plug-in ml-agent for unity [Electronic resource] // Access mode – https://habr.com/ru/post/416297/ (accessed 12.03.2020).

13. Unity ML-Agents Toolkit [Electronic resource] // Access mode – https://github.com/Unity-Technologies/ml-agents (accessed: 26.02.2020).

14. AI based on Unity ML Agents [Electronic resource] // Access mode – https://api-2d3d-cad.com/unity_ml_agents_quickstart/ (accessed: 07.03.2020).

15. Examples of creating an environment for training in ML-Agents [Electronic resource] // Access mode – https://github.com/Unity-Technologies/ml-agents/blob/release_2_docs/docs/Learning-Environment-Examples.md (accessed: 25.09.2020).

16. Creating Agents in ML-Agents [Electronic resource] // Access mode – https://github.com/Unity-Technologies/ml-agents/blob/release_2_docs/docs/Learning-Environment-Design-Agents.md

(accessed: 23.09.2020).

17. Examples of agent optimization in ML-Agents [Electronic resource] // Access mode – https://blogs.unity3d.com/ru/2019/11/11/training-your-agents-7-times-faster-with-ml-agents (accessed: 09.10.2020).

18. The creation of an environment in the ML-Agents [Electronic resource] // Access mode – https://github.com/Unity-Technologies/ml-agents/blob/release_2_docs/docs/Learning-Environment-Create-New.md (date of request: 11.10.2020).

19. Unity ML-Agents 1.0 - Training your first A. I. URL: [https://www.youtube.com/watch?v=_9aPZH6pyA8&ab_channel=Sebastian Schuchmann (accessed: 13.11.2020).



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