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Update README.md
Added a mention to the scientific article appeared on Nonlinear Dynamics in 2023
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README.md

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@@ -43,7 +43,11 @@ JSBSim is used in a range of projects among which:
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* Machine Learning Aircraft control: [gym-jsbsim](https://github.com/galleon/gym-jsbsim)
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* [DARPA Virtual Air Combat Competition](https://www.darpa.mil/news-events/2019-10-21) where one of the AI went undefeated in five rounds of mock air combat against an Air Force fighter (see the [video on YouTube](https://www.youtube.com/watch?v=IOJhgC1ksNU)).
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JSBSim is also used in academic and industry research ([more than 700 citations referenced by Google Scholar](https://scholar.google.com/scholar?&q=jsbsim) as of May 2022).
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## Academic and Industry Research
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JSBSim is also used in academic and industry research ([more than 700 citations referenced by Google Scholar](https://scholar.google.com/scholar?&q=jsbsim) as of May 2023).
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In 2023 JSBSim has been featured in the article ["A deep reinforcement learning control approach for high-performance aircraft"](https://link.springer.com/article/10.1007/s11071-023-08725-y) on _Nonlinear Dynamics_, an International Journal of Nonlinear Dynamics and Chaos in Engineering Systems by Springer. The open access article is available as a PDF here [https://link.springer.com/content/pdf/10.1007/s11071-023-08725-y.pdf](https://link.springer.com/content/pdf/10.1007/s11071-023-08725-y.pdf). The work demonstrates an application of Deep Reinforcement Learning (DRL) to flight control and guidance, leveraging the JSBSim interface to MATLAB/Simulink.
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# User Guide
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