المؤلفون: Muqing SU, Yin WANG, Ruimin PU, Meng YU

المصدر: 工程科学学报, Vol 46, Iss 7, Pp 1237-1250 (2024)

مصطلحات موضوعية: unmanned ground vehicles, cooperative encirclement, soft actor–critic algorithm, attention mechanism, reward function design, Mining engineering. Metallurgy, TN1-997, Environmental engineering, TA170-171

وصف الملف: electronic resource

Relation: https://doaj.org/toc/2095-9389

URL الوصول: https://doaj.org/article/c43b0a926b464906bf5794cd706c6bfb

المؤلفون: Li Long Xie, Yonghui Li, Peixiao Fan, Li Wan, Kanjun Zhang, Jun Yang

المصدر: IET Renewable Power Generation, Vol 18, Iss 7, Pp 1230-1246 (2024)

مصطلحات موضوعية: deep reinforcement learning controller, load frequency control, multi‐agent soft actor‐critic algorithm, multi‐microgrids system, Renewable energy sources, TJ807-830

وصف الملف: electronic resource

Relation: https://doaj.org/toc/1752-1416; https://doaj.org/toc/1752-1424

URL الوصول: https://doaj.org/article/45375a3a18974d54928cb9a96a249ed9

المؤلفون: Zhiwen Yu, Wenjie Zheng, Kaiwen Zeng, Ruifeng Zhao, Yanxu Zhang, Mengdi Zeng

المصدر: International Journal of Renewable Energy Development, Vol 13, Iss 2, Pp 329-339 (2024)

مصطلحات موضوعية: energy optimization management, electricity rate, microgrid, reinforcement learning, soft actor-critic algorithm, Renewable energy sources, TJ807-830

وصف الملف: electronic resource

Relation: https://ijred.cbiore.id/index.php/ijred/article/view/59988; https://doaj.org/toc/2252-4940

URL الوصول: https://doaj.org/article/3f7b72e8c3f64480b84a943d8124f3e2

المؤلفون: Zipeng Zhao, Yu Wan, Yong Chen

المصدر: Drones, Vol 8, Iss 9, p 464 (2024)

مصطلحات موضوعية: multi-UAV, obstacle avoidance, rounding-up, multi-agent deep reinforcement learning, soft actor–critic algorithm, Motor vehicles. Aeronautics. Astronautics, TL1-4050

وصف الملف: electronic resource

Relation: https://www.mdpi.com/2504-446X/8/9/464; https://doaj.org/toc/2504-446X

URL الوصول: https://doaj.org/article/8e6fd50aae6a4988b8ba43a53c414ce0

المؤلفون: Syed Muhammad Talha Zaidi, Pardha Sai Chadalavada, Hayat Ullah, Arslan Munir, Atri Dutta

المصدر: IEEE Access, Vol 11, Pp 82894-82911 (2023)

مصطلحات موضوعية: Deep reinforcement learning, cascaded reinforcement learning, soft actor-critic algorithm, spacecraft orbit-transfer, solar-electric propulsion, optimization, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/10207710/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/63bef6cf269a4615a8ed5578303f27cb

المؤلفون: FAN Jing-yu, LIU Quan

المصدر: Jisuanji kexue, Vol 49, Iss 6, Pp 335-341 (2022)

مصطلحات موضوعية: q-learning, deep learning, off-policy reinforcement learning, continuous action space, maximum entropy, soft actor critic algorithm, Computer software, QA76.75-76.765, Technology (General), T1-995

وصف الملف: electronic resource

Relation: https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-6-335.pdf; https://doaj.org/toc/1002-137X

URL الوصول: https://doaj.org/article/7a363b21497149698a570fcaf2d2ebad

المؤلفون: ZHANG Jia-neng, LI Hui, WU Hao-lin, WANG Zhuang

المصدر: Jisuanji kexue, Vol 49, Iss 5, Pp 179-185 (2022)

مصطلحات موضوعية: reinforcement learning, experience replay, priority sampling, exploitation, exploration, soft actor-critic algorithm, Computer software, QA76.75-76.765, Technology (General), T1-995

وصف الملف: electronic resource

Relation: https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-5-179.pdf; https://doaj.org/toc/1002-137X

URL الوصول: https://doaj.org/article/ff5d324d720443a899e77bc19f2a25d2

المؤلفون: Daeil Lee, Seoryong Koo, Inseok Jang, Jonghyun Kim

المصدر: Energies; Volume 15; Issue 8; Pages: 2834

مصطلحات موضوعية: nuclear power plant, autonomous operation, artificial intelligence, deep reinforcement learning, soft actor-critic algorithm

وصف الملف: application/pdf

Relation: B4: Nuclear Energy; https://dx.doi.org/10.3390/en15082834

الاتاحة: https://doi.org/10.3390/en15082834

المؤلفون: Stubel, Pascal

المساهمون: Erhard, Michael

مصطلحات موضوعية: Maschinelles Lernen, Reinforcement Learning, Soft-Acor-Critic Algorithmus, Gebäudeautomation, machine learning, soft-actor-critic algorithm, building automation, 600: Technik, ddc:600

وصف الملف: application/pdf

Relation: http://hdl.handle.net/20.500.12738/14311

الاتاحة: https://hdl.handle.net/20.500.12738/14311

المؤلفون: Carrera Escalé, Laura

المساهمون: Martín Muñoz, Mario, Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat de Barcelona, Universitat Rovira i Virgili

المصدر: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

مصطلحات موضوعية: safely drive, Mixture Density Recurrent Neural Network, Artificial Intelligence, Automobile driving simulators, Reinforcement learning, Aprenentatge per reforç, Automòbils -- Conducció -- Simuladors, Informàtica::Intel·ligència artificial [Àrees temàtiques de la UPC], Soft Actor-Critic algorithm, CARLA, Safety Mask, Autonomous Driving

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9b6c54529df810f9bcb71ceae333888b
http://hdl.handle.net/2117/348089

المؤلفون: 王衍晰, Wang, Yen-Hsi

المساهمون: 胡毓忠, Hu, Yuh-Jong

مصطلحات موضوعية: 深度強化學習, SAC 演算法, 投資組合, 資產配置, Deep Reinforcement Learning, Soft Actor-Critic Algorithm, Stock Portfolio, Portfolio Allocation

وصف الملف: 2894751 bytes; application/pdf

Relation: [1] T. M. Cover and E. Ordentlich, "Universal portfolios with side information," IEEE Transactions on Information Theory, vol. 42, no. 2, pp. 348-363, 1996.\n[2] S. Zhang, S. Wang, and X. Deng, "Portfolio selection theory with different interest rates for borrowing and leading," Journal of Global Optimization, vol. 28, no. 1, pp. 67-95, 2004.\n[3] B. Li and S. C. Hoi, "Online portfolio selection: A survey," ACM Computing Surveys (CSUR), vol. 46, no. 3, pp. 1-36, 2014.\n[4] F. D. Freitas, A. F. De Souza, and A. R. de Almeida, "Prediction-based portfolio optimization model using neural networks," Neurocomputing, vol. 72, no. 10-12, pp. 2155-2170, 2009.\n[5] S. T. A. Niaki and S. Hoseinzade, "Forecasting S&P 500 index using artificial neural networks and design of experiments," Journal of Industrial Engineering International, vol. 9, no. 1, p. 1, 2013.\n[6] J. Heaton, N. Polson, and J. H. Witte, "Deep learning for finance: deep portfolios," Applied Stochastic Models in Business and Industry, vol. 33, no. 1, pp. 3-12, 2017.\n[7] Z. Jiang, D. Xu, and J. Liang, "A deep reinforcement learning framework for the financial portfolio management problem," arXiv preprint arXiv:1706.10059, 2017.\n[8] T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine, "Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor," arXiv preprint arXiv:1801.01290, 2018.\n[9] T. Haarnoja et al., "Soft actor-critic algorithms and applications," arXiv preprint arXiv:1812.05905, 2018.\n[10] H. Markowitz, "Portfolio Selection The Journal of Finance, Vol. 7, No. 1," ed: Mar, 1952.\n[11] A.-H. Chang and J.-D. Kung, "Applying Grey forecasting model on the investment performance of Markowitz efficiency frontier: A case of the Taiwan securities markets," in First International Conference on Innovative Computing, Information and Control-Volume I (ICICIC`06), 2006, vol. 2, pp. 254-257: IEEE.\n[12] C.-F. Lee, A. C. Lee, and J. Lee, "Overview of Finance Theory and Quantitative Finance: Past, Present, and Future," 臺灣金融財務季刊, vol. 10, no. 4, pp. 1-85, 2009.\n[13] A. Agarwal, E. Hazan, S. Kale, and R. E. Schapire, "Algorithms for portfolio management based on the newton method," in Proceedings of the 23rd international conference on Machine learning, 2006, pp. 9-16.\n[14] Z. Jiang and J. Liang, "Cryptocurrency portfolio management with deep reinforcement learning," in 2017 Intelligent Systems Conference (IntelliSys), 2017, pp. 905-913: IEEE.\n[15] L. P. Kaelbling, M. L. Littman, and A. W. Moore, "Reinforcement learning: A survey," Journal of artificial intelligence research, vol. 4, pp. 237-285, 1996.\n[16] G. Tesauro, "TD-Gammon, a self-teaching backgammon program, achieves master-level play," Neural computation, vol. 6, no. 2, pp. 215-219, 1994.\n[17] M. I. Shapiai, Z. Ibrahim, M. Khalid, L. W. Jau, and V. Pavlovich, "A non-linear function approximation from small samples based on Nadaraya-Watson kernel regression," in 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks, 2010, pp. 28-32: IEEE.\n[18] T.-I. Tsai and D.-C. Li, "Approximate modeling for high order non-linear functions using small sample sets," Expert Systems with Applications, vol. 34, no. 1, pp. 564-569, 2008.\n[19] V. Mnih et al., "Playing atari with deep reinforcement learning," arXiv preprint arXiv:1312.5602, 2013.\n[20] T. P. Lillicrap et al., "Continuous control with deep reinforcement learning," arXiv preprint arXiv:1509.02971, 2015.\n[21] M. E. Mangram, "A simplified perspective of the Markowitz portfolio theory," Global journal of business research, vol. 7, no. 1, pp. 59-70, 2013.\n[22] Y. Deng, F. Bao, Y. Kong, Z. Ren, and Q. Dai, "Deep direct reinforcement learning for financial signal representation and trading," IEEE transactions on neural networks and learning systems, vol. 28, no. 3, pp. 653-664, 2016.\n[23] P. Nechchi, "Reinforcement Learning for Automated Trading," Mathematical EngineeringPolitecnico di Milano: Milano, Italy, 2016.\n[24] X. Li, Y. Li, Y. Zhan, and X.-Y. Liu, "Optimistic bull or pessimistic bear: adaptive deep reinforcement learning for stock portfolio allocation," arXiv preprint arXiv:1907.01503, 2019.\n[25] T. Haarnoja, S. Ha, A. Zhou, J. Tan, G. Tucker, and S. Levine, "Learning to walk via deep reinforcement learning," arXiv preprint arXiv:1812.11103, 2018.\n[26] Free Stock Charts, Stock Quotes, and Trade Ideas ─ TradingView (https://www.tradingview.com); G0104971008; https://nccur.lib.nccu.edu.tw//handle/140.119/131935; https://nccur.lib.nccu.edu.tw/bitstream/140.119/131935/1/100801.pdf

الاتاحة: https://nccur.lib.nccu.edu.tw//handle/140.119/131935
https://doi.org/10.6814/NCCU202001560
https://nccur.lib.nccu.edu.tw/bitstream/140.119/131935/1/100801.pdf

المؤلفون: Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat de Barcelona, Universitat Rovira i Virgili, Martín Muñoz, Mario, Carrera Escalé, Laura

مصطلحات الفهرس: Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial, Reinforcement learning, Automobile driving simulators, Autonomous Driving, Reinforcement Learning, Soft Actor-Critic algorithm, CARLA, Mixture Density Recurrent Neural Network, Safety Mask, safely drive, Artificial Intelligence, Aprenentatge per reforç, Automòbils -- Conducció -- Simuladors, Master thesis

URL: http://hdl.handle.net/2117/348089