Artículos de revistas sobre el tema "Safe Reinforcement Learning"
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Horie, Naoto, Tohgoroh Matsui, Koichi Moriyama, Atsuko Mutoh y Nobuhiro Inuzuka. "Multi-objective safe reinforcement learning: the relationship between multi-objective reinforcement learning and safe reinforcement learning". Artificial Life and Robotics 24, n.º 3 (8 de febrero de 2019): 352–59. http://dx.doi.org/10.1007/s10015-019-00523-3.
Texto completoYang, Yongliang, Kyriakos G. Vamvoudakis y Hamidreza Modares. "Safe reinforcement learning for dynamical games". International Journal of Robust and Nonlinear Control 30, n.º 9 (25 de marzo de 2020): 3706–26. http://dx.doi.org/10.1002/rnc.4962.
Texto completoXu, Haoran, Xianyuan Zhan y Xiangyu Zhu. "Constraints Penalized Q-learning for Safe Offline Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 8 (28 de junio de 2022): 8753–60. http://dx.doi.org/10.1609/aaai.v36i8.20855.
Texto completoGarcía, Javier y Fernando Fernández. "Probabilistic Policy Reuse for Safe Reinforcement Learning". ACM Transactions on Autonomous and Adaptive Systems 13, n.º 3 (28 de marzo de 2019): 1–24. http://dx.doi.org/10.1145/3310090.
Texto completoMannucci, Tommaso, Erik-Jan van Kampen, Cornelis de Visser y Qiping Chu. "Safe Exploration Algorithms for Reinforcement Learning Controllers". IEEE Transactions on Neural Networks and Learning Systems 29, n.º 4 (abril de 2018): 1069–81. http://dx.doi.org/10.1109/tnnls.2017.2654539.
Texto completoKarthikeyan, P., Wei-Lun Chen y Pao-Ann Hsiung. "Autonomous Intersection Management by Using Reinforcement Learning". Algorithms 15, n.º 9 (13 de septiembre de 2022): 326. http://dx.doi.org/10.3390/a15090326.
Texto completoMazouchi, Majid, Subramanya Nageshrao y Hamidreza Modares. "Conflict-Aware Safe Reinforcement Learning: A Meta-Cognitive Learning Framework". IEEE/CAA Journal of Automatica Sinica 9, n.º 3 (marzo de 2022): 466–81. http://dx.doi.org/10.1109/jas.2021.1004353.
Texto completoCowen-Rivers, Alexander I., Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang y Haitham Bou-Ammar. "SAMBA: safe model-based & active reinforcement learning". Machine Learning 111, n.º 1 (enero de 2022): 173–203. http://dx.doi.org/10.1007/s10994-021-06103-6.
Texto completoSerrano-Cuevas, Jonathan, Eduardo F. Morales y Pablo Hernández-Leal. "Safe reinforcement learning using risk mapping by similarity". Adaptive Behavior 28, n.º 4 (18 de julio de 2019): 213–24. http://dx.doi.org/10.1177/1059712319859650.
Texto completoAndersen, Per-Arne, Morten Goodwin y Ole-Christoffer Granmo. "Towards safe reinforcement-learning in industrial grid-warehousing". Information Sciences 537 (octubre de 2020): 467–84. http://dx.doi.org/10.1016/j.ins.2020.06.010.
Texto completoCarr, Steven, Nils Jansen, Sebastian Junges y Ufuk Topcu. "Safe Reinforcement Learning via Shielding under Partial Observability". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 12 (26 de junio de 2023): 14748–56. http://dx.doi.org/10.1609/aaai.v37i12.26723.
Texto completoDai, Juntao, Jiaming Ji, Long Yang, Qian Zheng y Gang Pan. "Augmented Proximal Policy Optimization for Safe Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 6 (26 de junio de 2023): 7288–95. http://dx.doi.org/10.1609/aaai.v37i6.25888.
Texto completoMarchesini, Enrico, Davide Corsi y Alessandro Farinelli. "Exploring Safer Behaviors for Deep Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 7 (28 de junio de 2022): 7701–9. http://dx.doi.org/10.1609/aaai.v36i7.20737.
Texto completoChen, Hongyi, Yu Zhang, Uzair Aslam Bhatti y Mengxing Huang. "Safe Decision Controller for Autonomous DrivingBased on Deep Reinforcement Learning inNondeterministic Environment". Sensors 23, n.º 3 (20 de enero de 2023): 1198. http://dx.doi.org/10.3390/s23031198.
Texto completoRyu, Yoon-Ha, Doukhi Oualid y Deok-Jin Lee. "Research on Safe Reinforcement Controller Using Deep Reinforcement Learning with Control Barrier Function". Journal of Institute of Control, Robotics and Systems 28, n.º 11 (30 de noviembre de 2022): 1013–21. http://dx.doi.org/10.5302/j.icros.2022.22.0187.
Texto completoThananjeyan, Brijen, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn y Ken Goldberg. "Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones". IEEE Robotics and Automation Letters 6, n.º 3 (julio de 2021): 4915–22. http://dx.doi.org/10.1109/lra.2021.3070252.
Texto completoCui, Wenqi, Jiayi Li y Baosen Zhang. "Decentralized safe reinforcement learning for inverter-based voltage control". Electric Power Systems Research 211 (octubre de 2022): 108609. http://dx.doi.org/10.1016/j.epsr.2022.108609.
Texto completoBasso, Rafael, Balázs Kulcsár, Ivan Sanchez-Diaz y Xiaobo Qu. "Dynamic stochastic electric vehicle routing with safe reinforcement learning". Transportation Research Part E: Logistics and Transportation Review 157 (enero de 2022): 102496. http://dx.doi.org/10.1016/j.tre.2021.102496.
Texto completoPai, PENG, ZHU Fei, LIU Quan, ZHAO Peiyao y WU Wen. "Achieving Safe Deep Reinforcement Learning via Environment Comprehension Mechanism". Chinese Journal of Electronics 30, n.º 6 (noviembre de 2021): 1049–58. http://dx.doi.org/10.1049/cje.2021.07.025.
Texto completoMowbray, M., P. Petsagkourakis, E. A. del Rio-Chanona y D. Zhang. "Safe chance constrained reinforcement learning for batch process control". Computers & Chemical Engineering 157 (enero de 2022): 107630. http://dx.doi.org/10.1016/j.compchemeng.2021.107630.
Texto completoZhao, Qingye, Yi Zhang y Xuandong Li. "Safe reinforcement learning for dynamical systems using barrier certificates". Connection Science 34, n.º 1 (12 de diciembre de 2022): 2822–44. http://dx.doi.org/10.1080/09540091.2022.2151567.
Texto completoGros, Sebastien, Mario Zanon y Alberto Bemporad. "Safe Reinforcement Learning via Projection on a Safe Set: How to Achieve Optimality?" IFAC-PapersOnLine 53, n.º 2 (2020): 8076–81. http://dx.doi.org/10.1016/j.ifacol.2020.12.2276.
Texto completoLu, Xiaozhen, Liang Xiao, Guohang Niu, Xiangyang Ji y Qian Wang. "Safe Exploration in Wireless Security: A Safe Reinforcement Learning Algorithm With Hierarchical Structure". IEEE Transactions on Information Forensics and Security 17 (2022): 732–43. http://dx.doi.org/10.1109/tifs.2022.3149396.
Texto completoYuan, Zhaocong, Adam W. Hall, Siqi Zhou, Lukas Brunke, Melissa Greeff, Jacopo Panerati y Angela P. Schoellig. "Safe-Control-Gym: A Unified Benchmark Suite for Safe Learning-Based Control and Reinforcement Learning in Robotics". IEEE Robotics and Automation Letters 7, n.º 4 (octubre de 2022): 11142–49. http://dx.doi.org/10.1109/lra.2022.3196132.
Texto completoGarcia, J. y F. Fernandez. "Safe Exploration of State and Action Spaces in Reinforcement Learning". Journal of Artificial Intelligence Research 45 (19 de diciembre de 2012): 515–64. http://dx.doi.org/10.1613/jair.3761.
Texto completoMa, Yecheng Jason, Andrew Shen, Osbert Bastani y Jayaraman Dinesh. "Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 5 (28 de junio de 2022): 5404–12. http://dx.doi.org/10.1609/aaai.v36i5.20478.
Texto completoChen, Hongyi y Changliu Liu. "Safe and Sample-Efficient Reinforcement Learning for Clustered Dynamic Environments". IEEE Control Systems Letters 6 (2022): 1928–33. http://dx.doi.org/10.1109/lcsys.2021.3136486.
Texto completoYang, Yongliang, Kyriakos G. Vamvoudakis, Hamidreza Modares, Yixin Yin y Donald C. Wunsch. "Safe Intermittent Reinforcement Learning With Static and Dynamic Event Generators". IEEE Transactions on Neural Networks and Learning Systems 31, n.º 12 (diciembre de 2020): 5441–55. http://dx.doi.org/10.1109/tnnls.2020.2967871.
Texto completoLi, Hepeng, Zhiqiang Wan y Haibo He. "Constrained EV Charging Scheduling Based on Safe Deep Reinforcement Learning". IEEE Transactions on Smart Grid 11, n.º 3 (mayo de 2020): 2427–39. http://dx.doi.org/10.1109/tsg.2019.2955437.
Texto completoHailemichael, Habtamu, Beshah Ayalew, Lindsey Kerbel, Andrej Ivanco y Keith Loiselle. "Safe Reinforcement Learning for an Energy-Efficient Driver Assistance System". IFAC-PapersOnLine 55, n.º 37 (2022): 615–20. http://dx.doi.org/10.1016/j.ifacol.2022.11.250.
Texto completoMINAMOTO, Gaku, Toshimitsu KANEKO y Noriyuki HIRAYAMA. "Autonomous driving with safe reinforcement learning using rule-based judgment". Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2022 (2022): 2A2—K03. http://dx.doi.org/10.1299/jsmermd.2022.2a2-k03.
Texto completoPathak, Shashank, Luca Pulina y Armando Tacchella. "Verification and repair of control policies for safe reinforcement learning". Applied Intelligence 48, n.º 4 (5 de agosto de 2017): 886–908. http://dx.doi.org/10.1007/s10489-017-0999-8.
Texto completoDong, Wenbo, Shaofan Liu y Shiliang Sun. "Safe batch constrained deep reinforcement learning with generative adversarial network". Information Sciences 634 (julio de 2023): 259–70. http://dx.doi.org/10.1016/j.ins.2023.03.108.
Texto completoKondrup, Flemming, Thomas Jiralerspong, Elaine Lau, Nathan De Lara, Jacob Shkrob, My Duc Tran, Doina Precup y Sumana Basu. "Towards Safe Mechanical Ventilation Treatment Using Deep Offline Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 13 (26 de junio de 2023): 15696–702. http://dx.doi.org/10.1609/aaai.v37i13.26862.
Texto completoFu, Yanbo, Wenjie Zhao y Liu Liu. "Safe Reinforcement Learning for Transition Control of Ducted-Fan UAVs". Drones 7, n.º 5 (22 de mayo de 2023): 332. http://dx.doi.org/10.3390/drones7050332.
Texto completoXiao, Xinhang. "Reinforcement Learning Optimized Intelligent Electricity Dispatching System". Journal of Physics: Conference Series 2215, n.º 1 (1 de febrero de 2022): 012013. http://dx.doi.org/10.1088/1742-6596/2215/1/012013.
Texto completoYOON, JAE UNG y JUHONG LEE. "Uncertainty Sequence Modeling Approach for Safe and Effective Autonomous Driving". Korean Institute of Smart Media 11, n.º 9 (31 de octubre de 2022): 9–20. http://dx.doi.org/10.30693/smj.2022.11.9.9.
Texto completoPerk, Baris Eren y Gokhan Inalhan. "Safe Motion Planning and Learning for Unmanned Aerial Systems". Aerospace 9, n.º 2 (22 de enero de 2022): 56. http://dx.doi.org/10.3390/aerospace9020056.
Texto completoUgurlu, Halil Ibrahim, Xuan Huy Pham y Erdal Kayacan. "Sim-to-Real Deep Reinforcement Learning for Safe End-to-End Planning of Aerial Robots". Robotics 11, n.º 5 (13 de octubre de 2022): 109. http://dx.doi.org/10.3390/robotics11050109.
Texto completoLu, Songtao, Kaiqing Zhang, Tianyi Chen, Tamer Başar y Lior Horesh. "Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 10 (18 de mayo de 2021): 8767–75. http://dx.doi.org/10.1609/aaai.v35i10.17062.
Texto completoJi, Guanglin, Junyan Yan, Jingxin Du, Wanquan Yan, Jibiao Chen, Yongkang Lu, Juan Rojas y Shing Shin Cheng. "Towards Safe Control of Continuum Manipulator Using Shielded Multiagent Reinforcement Learning". IEEE Robotics and Automation Letters 6, n.º 4 (octubre de 2021): 7461–68. http://dx.doi.org/10.1109/lra.2021.3097660.
Texto completoSavage, Thomas, Dongda Zhang, Max Mowbray y Ehecatl Antonio Del Río Chanona. "Model-free safe reinforcement learning for chemical processes using Gaussian processes". IFAC-PapersOnLine 54, n.º 3 (2021): 504–9. http://dx.doi.org/10.1016/j.ifacol.2021.08.292.
Texto completoDu, Bin, Bin Lin, Chenming Zhang, Botao Dong y Weidong Zhang. "Safe deep reinforcement learning-based adaptive control for USV interception mission". Ocean Engineering 246 (febrero de 2022): 110477. http://dx.doi.org/10.1016/j.oceaneng.2021.110477.
Texto completoKim, Dohyeong y Songhwai Oh. "TRC: Trust Region Conditional Value at Risk for Safe Reinforcement Learning". IEEE Robotics and Automation Letters 7, n.º 2 (abril de 2022): 2621–28. http://dx.doi.org/10.1109/lra.2022.3141829.
Texto completoGarcía, Javier y Diogo Shafie. "Teaching a humanoid robot to walk faster through Safe Reinforcement Learning". Engineering Applications of Artificial Intelligence 88 (febrero de 2020): 103360. http://dx.doi.org/10.1016/j.engappai.2019.103360.
Texto completoCohen, Max H. y Calin Belta. "Safe exploration in model-based reinforcement learning using control barrier functions". Automatica 147 (enero de 2023): 110684. http://dx.doi.org/10.1016/j.automatica.2022.110684.
Texto completoSelvaraj, Dinesh Cyril, Shailesh Hegde, Nicola Amati, Francesco Deflorio y Carla Fabiana Chiasserini. "A Deep Reinforcement Learning Approach for Efficient, Safe and Comfortable Driving". Applied Sciences 13, n.º 9 (23 de abril de 2023): 5272. http://dx.doi.org/10.3390/app13095272.
Texto completoVasilenko, Elizaveta, Niki Vazou y Gilles Barthe. "Safe couplings: coupled refinement types". Proceedings of the ACM on Programming Languages 6, ICFP (29 de agosto de 2022): 596–624. http://dx.doi.org/10.1145/3547643.
Texto completoXiao, Wenli, Yiwei Lyu y John M. Dolan. "Tackling Safe and Efficient Multi-Agent Reinforcement Learning via Dynamic Shielding (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 13 (26 de junio de 2023): 16362–63. http://dx.doi.org/10.1609/aaai.v37i13.27041.
Texto completoYang, Yanhua y Ligang Yao. "Optimization Method of Power Equipment Maintenance Plan Decision-Making Based on Deep Reinforcement Learning". Mathematical Problems in Engineering 2021 (15 de marzo de 2021): 1–8. http://dx.doi.org/10.1155/2021/9372803.
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