RL-based Control of Smart Base Isolation System Using Unity ML-Agents
Author:
Funder
National Research Foundation of Korea
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13296-024-00862-3.pdf
Reference22 articles.
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2. Fuchs, A., Heider, Y., Wang, K., Sun, W., & Kaliske, M. (2021). DNN2: A hyper-parameter reinforcement learning game for self-design of neural network based elasto-plastic constitutive descriptions. Computers & Structures, 249, 106505. https://doi.org/10.1016/j.compstruc.2021.106505
3. Hussein, A., García, F., & Olaverri-Monreal, C. (2018). ROS and Unity Based Framework for Intelligent Vehicles Control and Simulation, In 2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES), Madrid, Spain, pp. 1–6, https://doi.org/10.1109/ICVES.2018.8519522
4. Huynh, T. N., Do, D., & Lee, J. (2021). Q-Learning-based parameter control in differential evolution for structural optimization. Applied Soft Computing, 107, 107464. https://doi.org/10.1016/j.asoc.2021.107464
5. Khalatbarisoltani, A., Soleymani, M., & Khodadadi, M. (2019). Online control of an active seismic system via reinforcement learning. Structural Control and Health Monitoring, 26, e2298.
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