Academic literature on the topic 'Constrained RL'
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Journal articles on the topic "Constrained RL"
HasanzadeZonuzy, Aria, Archana Bura, Dileep Kalathil, and Srinivas Shakkottai. "Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (May 18, 2021): 7667–74. http://dx.doi.org/10.1609/aaai.v35i9.16937.
Full textZhang, Renchi, Runsheng Yu, and Wei Xia. "Constraint-aware Policy Optimization to Solve the Vehicle Routing Problem with Time Windows." Information Technology and Control 51, no. 1 (March 26, 2022): 126–38. http://dx.doi.org/10.5755/j01.itc.51.1.29924.
Full textHu, Jingwei, Zhu Liu, Chichuan Jin, and Weimin Yuan. "Relativistic Fe Kα line in the composite X-ray spectra of radio-loud active galactic nuclei." Monthly Notices of the Royal Astronomical Society 488, no. 3 (July 25, 2019): 4378–88. http://dx.doi.org/10.1093/mnras/stz2030.
Full textBhatia, Abhinav, Pradeep Varakantham, and Akshat Kumar. "Resource Constrained Deep Reinforcement Learning." Proceedings of the International Conference on Automated Planning and Scheduling 29 (May 25, 2021): 610–20. http://dx.doi.org/10.1609/icaps.v29i1.3528.
Full textGu, Shangding, Guang Chen, Lijun Zhang, Jing Hou, Yingbai Hu, and Alois Knoll. "Constrained Reinforcement Learning for Vehicle Motion Planning with Topological Reachability Analysis." Robotics 11, no. 4 (August 16, 2022): 81. http://dx.doi.org/10.3390/robotics11040081.
Full textWang, Ru-Min, Jin-Huan Sheng, Jie Zhu, Ying-Ying Fan, and Yuan-Guo Xu. "Decays $D^+_{(s)}\to \pi(K)^{+}\ell^+\ell^-$ and D0→ℓ+ℓ- in the MSSM with and without R-parity." International Journal of Modern Physics A 30, no. 12 (April 28, 2015): 1550063. http://dx.doi.org/10.1142/s0217751x15500633.
Full textWei, Honghao, Xin Liu, and Lei Ying. "A Provably-Efficient Model-Free Algorithm for Infinite-Horizon Average-Reward Constrained Markov Decision Processes." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (June 28, 2022): 3868–76. http://dx.doi.org/10.1609/aaai.v36i4.20302.
Full textLee, Xian Yeow, Sambit Ghadai, Kai Liang Tan, Chinmay Hegde, and Soumik Sarkar. "Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 4577–84. http://dx.doi.org/10.1609/aaai.v34i04.5887.
Full textDelgrange, Florent, Ann Nowé, and Guillermo A. Pérez. "Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (June 28, 2022): 6497–505. http://dx.doi.org/10.1609/aaai.v36i6.20602.
Full textDing, Zhenhuan, Xiaoge Huang, and Zhao Liu. "Active Exploration by Chance-Constrained Optimization for Voltage Regulation with Reinforcement Learning." Energies 15, no. 2 (January 16, 2022): 614. http://dx.doi.org/10.3390/en15020614.
Full textBooks on the topic "Constrained RL"
Denneheuvel, Sieger van. Constraint solving on data base systems: Design and implementation of the rule language RL/1. [Netherlands: s.n., 1991.
Find full textBook chapters on the topic "Constrained RL"
Du, Zhiyong, Bin Jiang, Qihui Wu, Yuhua Xu, and Kun Xu. "Learning the Optimal Network with Handoff Constraint: MAB RL Based Network Selection." In Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks, 13–31. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1120-2_2.
Full textSadeghi, Saeid, Maghsoud Amiri, and Farzaneh Mansoori Mooseloo. "Artificial Intelligence and Its Application in Optimization under Uncertainty." In Artificial Intelligence. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98628.
Full textDaneshfar, Fatemeh, and Vafa Maihami. "Distributed Learning Algorithm Applications to the Scheduling of Wireless Sensor Networks." In Mobile Computing and Wireless Networks, 1049–81. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8751-6.ch045.
Full textDaneshfar, Fatemeh, and Vafa Maihami. "Distributed Learning Algorithm Applications to the Scheduling of Wireless Sensor Networks." In Handbook of Research on Novel Soft Computing Intelligent Algorithms, 860–91. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4450-2.ch028.
Full textConference papers on the topic "Constrained RL"
Sarafian, Elad, Aviv Tamar, and Sarit Kraus. "Constrained Policy Improvement for Efficient Reinforcement Learning." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/396.
Full textWang, Zhaorong, Meng Wang, Jingqi Zhang, Yingfeng Chen, and Chongjie Zhang. "Reward-Constrained Behavior Cloning." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/436.
Full textPeruvemba, Yasasvi V., Shubham Rai, Kapil Ahuja, and Akash Kumar. "RL-Guided Runtime-Constrained Heuristic Exploration for Logic Synthesis." In 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD). IEEE, 2021. http://dx.doi.org/10.1109/iccad51958.2021.9643530.
Full textHasanzadeZonuzy, Aria, Dileep Kalathil, and Srinivas Shakkottai. "Model-Based Reinforcement Learning for Infinite-Horizon Discounted Constrained Markov Decision Processes." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/347.
Full textLiu, Yongshuai, Avishai Halev, and Xin Liu. "Policy Learning with Constraints in Model-free Reinforcement Learning: A Survey." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/614.
Full textAlonso, Eloi, Maxim Peter, David Goumard, and Joshua Romoff. "Deep Reinforcement Learning for Navigation in AAA Video Games." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/294.
Full textJiang, Di, Yuan Cao, and Qiang Yang. "On the Channel Pruning using Graph Convolution Network for Convolutional Neural Network Acceleration." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/431.
Full textBack, Philipp. "Real-World Reinforcement Learning: Observations from Two Successful Cases." In Digital Support from Crisis to Progressive Change. University of Maribor Press, 2021. http://dx.doi.org/10.18690/978-961-286-485-9.20.
Full textSohn, Sungryull, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, and Craig Boutilier. "BRPO: Batch Residual Policy Optimization." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/391.
Full textFedullo, Tommaso, Alberto Morato, Federico Tramarin, Paolo Ferrari, and Emiliano Sisinni. "Smart Measurement Systems Exploiting Adaptive LoRaWAN Under Power Consumption Constraints: a RL Approach." In 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT). IEEE, 2022. http://dx.doi.org/10.1109/metroind4.0iot54413.2022.9831487.
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