Artículos de revistas sobre el tema "Improper reinforcement learning"
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Dass, Shuvalaxmi y Akbar Siami Namin. "Reinforcement Learning for Generating Secure Configurations". Electronics 10, n.º 19 (30 de septiembre de 2021): 2392. http://dx.doi.org/10.3390/electronics10192392.
Texto completoZhai, Peng, Jie Luo, Zhiyan Dong, Lihua Zhang, Shunli Wang y Dingkang Yang. "Robust Adversarial Reinforcement Learning with Dissipation Inequation Constraint". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 5 (28 de junio de 2022): 5431–39. http://dx.doi.org/10.1609/aaai.v36i5.20481.
Texto completoChen, Ya-Ling, Yan-Rou Cai y Ming-Yang Cheng. "Vision-Based Robotic Object Grasping—A Deep Reinforcement Learning Approach". Machines 11, n.º 2 (12 de febrero de 2023): 275. http://dx.doi.org/10.3390/machines11020275.
Texto completoHurtado-Gómez, Julián, Juan David Romo, Ricardo Salazar-Cabrera, Álvaro Pachón de la Cruz y Juan Manuel Madrid Molina. "Traffic Signal Control System Based on Intelligent Transportation System and Reinforcement Learning". Electronics 10, n.º 19 (28 de septiembre de 2021): 2363. http://dx.doi.org/10.3390/electronics10192363.
Texto completoZiwei Pan, Ziwei Pan. "Design of Interactive Cultural Brand Marketing System based on Cloud Service Platform". 網際網路技術學刊 23, n.º 2 (marzo de 2022): 321–34. http://dx.doi.org/10.53106/160792642022032302012.
Texto completoKim, Byeongjun, Gunam Kwon, Chaneun Park y Nam Kyu Kwon. "The Task Decomposition and Dedicated Reward-System-Based Reinforcement Learning Algorithm for Pick-and-Place". Biomimetics 8, n.º 2 (6 de junio de 2023): 240. http://dx.doi.org/10.3390/biomimetics8020240.
Texto completoRitonga, Mahyudin y Fitria Sartika. "Muyûl al-Talâmidh fî Tadrîs al-Qirâ’ah". Jurnal Alfazuna : Jurnal Pembelajaran Bahasa Arab dan Kebahasaaraban 6, n.º 1 (21 de diciembre de 2021): 36–52. http://dx.doi.org/10.15642/alfazuna.v6i1.1715.
Texto completoLikas, Aristidis. "A Reinforcement Learning Approach to Online Clustering". Neural Computation 11, n.º 8 (1 de noviembre de 1999): 1915–32. http://dx.doi.org/10.1162/089976699300016025.
Texto completoYing-Ming Shi, Ying-Ming Shi y Zhiyuan Zhang Ying-Ming Shi. "Research on Path Planning Strategy of Rescue Robot Based on Reinforcement Learning". 電腦學刊 33, n.º 3 (junio de 2022): 187–94. http://dx.doi.org/10.53106/199115992022063303015.
Texto completoSantos, John Paul E., Joseph A. Villarama, Joseph P. Adsuara, Jordan F. Gundran, Aileen G. De Guzman y Evelyn M. Ben. "Students’ Time Management, Academic Procrastination, and Performance during Online Science and Mathematics Classes". International Journal of Learning, Teaching and Educational Research 21, n.º 12 (30 de diciembre de 2022): 142–61. http://dx.doi.org/10.26803/ijlter.21.12.8.
Texto completoMinghai Yuan, Minghai Yuan, Chenxi Zhang Minghai Yuan, Kaiwen Zhou Chenxi Zhang y Fengque Pei Kaiwen Zhou. "Real-time Allocation of Shared Parking Spaces Based on Deep Reinforcement Learning". 網際網路技術學刊 24, n.º 1 (enero de 2023): 035–43. http://dx.doi.org/10.53106/160792642023012401004.
Texto completoWest, Joseph, Frederic Maire, Cameron Browne y Simon Denman. "Improved reinforcement learning with curriculum". Expert Systems with Applications 158 (noviembre de 2020): 113515. http://dx.doi.org/10.1016/j.eswa.2020.113515.
Texto completoZini, Floriano, Fabio Le Piane y Mauro Gaspari. "Adaptive Cognitive Training with Reinforcement Learning". ACM Transactions on Interactive Intelligent Systems 12, n.º 1 (31 de marzo de 2022): 1–29. http://dx.doi.org/10.1145/3476777.
Texto completoChen, Junyan, Yong Wang, Jiangtao Ou, Chengyuan Fan, Xiaoye Lu, Cenhuishan Liao, Xuefeng Huang y Hongmei Zhang. "ALBRL: Automatic Load-Balancing Architecture Based on Reinforcement Learning in Software-Defined Networking". Wireless Communications and Mobile Computing 2022 (2 de mayo de 2022): 1–17. http://dx.doi.org/10.1155/2022/3866143.
Texto completoTessler, Chen, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik y Shie Mannor. "Reinforcement Learning for Datacenter Congestion Control". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 11 (28 de junio de 2022): 12615–21. http://dx.doi.org/10.1609/aaai.v36i11.21535.
Texto completoTessler, Chen, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik y Shie Mannor. "Reinforcement Learning for Datacenter Congestion Control". ACM SIGMETRICS Performance Evaluation Review 49, n.º 2 (17 de enero de 2022): 43–46. http://dx.doi.org/10.1145/3512798.3512815.
Texto completoLittman, Michael L. "Reinforcement learning improves behaviour from evaluative feedback". Nature 521, n.º 7553 (mayo de 2015): 445–51. http://dx.doi.org/10.1038/nature14540.
Texto completoYen-Wen Chen, Yen-Wen Chen y Ji-Zheng You Yen-Wen Chen. "Effective Radio Resource Allocation for IoT Random Access by Using Reinforcement Learning". 網際網路技術學刊 23, n.º 5 (septiembre de 2022): 1069–75. http://dx.doi.org/10.53106/160792642022092305015.
Texto completoZhao, Yongqi, Zhangdong Wei y Jing Wen. "Prediction of Soil Heavy Metal Content Based on Deep Reinforcement Learning". Scientific Programming 2022 (15 de abril de 2022): 1–10. http://dx.doi.org/10.1155/2022/1476565.
Texto completoMcLaverty, Brian, Robert S. Parker y Gilles Clermont. "Reinforcement learning algorithm to improve intermittent hemodialysis". Journal of Critical Care 74 (abril de 2023): 154205. http://dx.doi.org/10.1016/j.jcrc.2022.154205.
Texto completoLin, Jin. "Path planning based on reinforcement learning". Applied and Computational Engineering 5, n.º 1 (14 de junio de 2023): 853–58. http://dx.doi.org/10.54254/2755-2721/5/20230728.
Texto completoHuang, Xu, Hong Zhang y Xiaomeng Zhai. "A Novel Reinforcement Learning Approach for Spark Configuration Parameter Optimization". Sensors 22, n.º 15 (8 de agosto de 2022): 5930. http://dx.doi.org/10.3390/s22155930.
Texto completoIssa, A. y A. Aldair. "Learning the Quadruped Robot by Reinforcement Learning (RL)". Iraqi Journal for Electrical and Electronic Engineering 18, n.º 2 (6 de octubre de 2022): 117–26. http://dx.doi.org/10.37917/ijeee.18.2.15.
Texto completoZhao, Yuxin, Yanlong Liu y Xiong Deng. "Optimization of a Regional Marine Environment Mobile Observation Network Based on Deep Reinforcement Learning". Journal of Marine Science and Engineering 11, n.º 1 (12 de enero de 2023): 208. http://dx.doi.org/10.3390/jmse11010208.
Texto completoLecarpentier, Erwan, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson y Michael L. Littman. "Lipschitz Lifelong Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 9 (18 de mayo de 2021): 8270–78. http://dx.doi.org/10.1609/aaai.v35i9.17006.
Texto completoLiu, Yu y Ning Zhou. "Jumping Action Recognition for Figure Skating Video in IoT Using Improved Deep Reinforcement Learning". Information Technology and Control 52, n.º 2 (15 de julio de 2023): 309–21. http://dx.doi.org/10.5755/j01.itc.52.2.33300.
Texto completoGonzález-Garduño, Ana V. "Reinforcement Learning for Improved Low Resource Dialogue Generation". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 9884–85. http://dx.doi.org/10.1609/aaai.v33i01.33019884.
Texto completoKuremoto, Takashi, Tetsuya Tsurusaki, Kunikazu Kobayashi, Shingo Mabu y Masanao Obayashi. "An Improved Reinforcement Learning System Using Affective Factors". Robotics 2, n.º 3 (10 de julio de 2013): 149–64. http://dx.doi.org/10.3390/robotics2030149.
Texto completoLuo, Teng. "Improved reinforcement learning algorithm for mobile robot path planning". ITM Web of Conferences 47 (2022): 02030. http://dx.doi.org/10.1051/itmconf/20224702030.
Texto completoWu, Yukun, Xuncheng Wu, Siyuan Qiu y Wenbin Xiang. "A Method for High-Value Driving Demonstration Data Generation Based on One-Dimensional Deep Convolutional Generative Adversarial Networks". Electronics 11, n.º 21 (31 de octubre de 2022): 3553. http://dx.doi.org/10.3390/electronics11213553.
Texto completoMaree, Charl y Christian W. Omlin. "Can Interpretable Reinforcement Learning Manage Prosperity Your Way?" AI 3, n.º 2 (13 de junio de 2022): 526–37. http://dx.doi.org/10.3390/ai3020030.
Texto completoFang, Qiang, Wenzhuo Zhang y Xitong Wang. "Visual Navigation Using Inverse Reinforcement Learning and an Extreme Learning Machine". Electronics 10, n.º 16 (18 de agosto de 2021): 1997. http://dx.doi.org/10.3390/electronics10161997.
Texto completoOmidshafiei, Shayegan, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell y Jonathan P. How. "Learning to Teach in Cooperative Multiagent Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 6128–36. http://dx.doi.org/10.1609/aaai.v33i01.33016128.
Texto completoMa, Guoqing, Zhifu Wang, Xianfeng Yuan y Fengyu Zhou. "Improving Model-Based Deep Reinforcement Learning with Learning Degree Networks and Its Application in Robot Control". Journal of Robotics 2022 (4 de marzo de 2022): 1–14. http://dx.doi.org/10.1155/2022/7169594.
Texto completoFRIEDRICH, JOHANNES, ROBERT URBANCZIK y WALTER SENN. "CODE-SPECIFIC LEARNING RULES IMPROVE ACTION SELECTION BY POPULATIONS OF SPIKING NEURONS". International Journal of Neural Systems 24, n.º 05 (30 de mayo de 2014): 1450002. http://dx.doi.org/10.1142/s0129065714500026.
Texto completoRen, Jing, Xishi Huang y Raymond N. Huang. "Efficient Deep Reinforcement Learning for Optimal Path Planning". Electronics 11, n.º 21 (7 de noviembre de 2022): 3628. http://dx.doi.org/10.3390/electronics11213628.
Texto completoBai, Fengshuo, Hongming Zhang, Tianyang Tao, Zhiheng Wu, Yanna Wang y Bo Xu. "PiCor: Multi-Task Deep Reinforcement Learning with Policy Correction". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 6 (26 de junio de 2023): 6728–36. http://dx.doi.org/10.1609/aaai.v37i6.25825.
Texto completoZajdel, Roman. "Epoch-incremental reinforcement learning algorithms". International Journal of Applied Mathematics and Computer Science 23, n.º 3 (1 de septiembre de 2013): 623–35. http://dx.doi.org/10.2478/amcs-2013-0047.
Texto completoYu, Ning, Lin Nan y Tao Ku. "Multipolicy Robot-Following Model Based on Reinforcement Learning". Scientific Programming 2021 (8 de noviembre de 2021): 1–8. http://dx.doi.org/10.1155/2021/5692105.
Texto completoZhou, Minghui. "Multithreshold Microbial Image Segmentation Using Improved Deep Reinforcement Learning". Mathematical Problems in Engineering 2022 (23 de agosto de 2022): 1–11. http://dx.doi.org/10.1155/2022/5096298.
Texto completoKaddour, N., P. Del Moral y E. Ikonen. "Improved version of the McMurtry-Fu reinforcement learning scheme". International Journal of Systems Science 34, n.º 1 (enero de 2003): 37–47. http://dx.doi.org/10.1080/0020772031000115560.
Texto completoShi, Zhen, Keyin Wang y Jianhui Zhang. "Improved reinforcement learning path planning algorithm integrating prior knowledge". PLOS ONE 18, n.º 5 (4 de mayo de 2023): e0284942. http://dx.doi.org/10.1371/journal.pone.0284942.
Texto completoBéres, András y Bálint Gyires-Tóth. "Enhancing Visual Domain Randomization with Real Images for Sim-to-Real Transfer". Infocommunications journal 15, n.º 1 (2023): 15–25. http://dx.doi.org/10.36244/icj.2023.1.3.
Texto completoSzepesvári, Csaba y Michael L. Littman. "A Unified Analysis of Value-Function-Based Reinforcement-Learning Algorithms". Neural Computation 11, n.º 8 (1 de noviembre de 1999): 2017–60. http://dx.doi.org/10.1162/089976699300016070.
Texto completoHuang, Yong, Xin Xu, Yong Li, Xinglong Zhang, Yao Liu y Xiaochuan Zhang. "Vehicle-Following Control Based on Deep Reinforcement Learning". Applied Sciences 12, n.º 20 (21 de octubre de 2022): 10648. http://dx.doi.org/10.3390/app122010648.
Texto completoJiang, Huawei, Tao Guo, Zhen Yang y Like Zhao. "Deep reinforcement learning algorithm for solving material emergency dispatching problem". Mathematical Biosciences and Engineering 19, n.º 11 (2022): 10864–81. http://dx.doi.org/10.3934/mbe.2022508.
Texto completoKoga, Marcelo L., Valdinei Freire y Anna H. R. Costa. "Stochastic Abstract Policies: Generalizing Knowledge to Improve Reinforcement Learning". IEEE Transactions on Cybernetics 45, n.º 1 (enero de 2015): 77–88. http://dx.doi.org/10.1109/tcyb.2014.2319733.
Texto completoLi, Xiali, Zhengyu Lv, Licheng Wu, Yue Zhao y Xiaona Xu. "Hybrid Online and Offline Reinforcement Learning for Tibetan Jiu Chess". Complexity 2020 (11 de mayo de 2020): 1–11. http://dx.doi.org/10.1155/2020/4708075.
Texto completoTantu, Year Rezeki Patricia y Kirey Eleison Oloi Marina. "Teachers' efforts to improve discipline of elementary school students using positive reinforcement methods in online learning". JURNAL PENDIDIKAN DASAR NUSANTARA 8, n.º 2 (31 de enero de 2023): 288–98. http://dx.doi.org/10.29407/jpdn.v8i2.19118.
Texto completoHuang, Wenya, Youjin Liu y Xizheng Zhang. "Hybrid Particle Swarm Optimization Algorithm Based on the Theory of Reinforcement Learning in Psychology". Systems 11, n.º 2 (6 de febrero de 2023): 83. http://dx.doi.org/10.3390/systems11020083.
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