Artigos de revistas sobre o tema "Constrained exploration"
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Pankayaraj, Pathmanathan, e Pradeep Varakantham. "Constrained Reinforcement Learning in Hard Exploration Problems". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 12 (26 de junho de 2023): 15055–63. http://dx.doi.org/10.1609/aaai.v37i12.26757.
Texto completo da fonteMellado, Nicolas, David Vanderhaeghe, Charlotte Hoarau, Sidonie Christophe, Mathieu Brédif e Loic Barthe. "Constrained palette-space exploration". ACM Transactions on Graphics 36, n.º 4 (20 de julho de 2017): 1–14. http://dx.doi.org/10.1145/3072959.3073650.
Texto completo da fonteDuncan, Christian A., Stephen G. Kobourov e V. S. Anil Kumar. "Optimal constrained graph exploration". ACM Transactions on Algorithms 2, n.º 3 (julho de 2006): 380–402. http://dx.doi.org/10.1145/1159892.1159897.
Texto completo da fonteYang, Qisong, e Matthijs T. J. Spaan. "CEM: Constrained Entropy Maximization for Task-Agnostic Safe Exploration". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 9 (26 de junho de 2023): 10798–806. http://dx.doi.org/10.1609/aaai.v37i9.26281.
Texto completo da fonteIvanov, Alexander, e Mark Campbell. "Uncertainty Constrained Robotic Exploration: An Integrated Exploration Planner". IEEE Transactions on Control Systems Technology 27, n.º 1 (janeiro de 2019): 146–60. http://dx.doi.org/10.1109/tcst.2017.2759729.
Texto completo da fonteAhuir, J., A. S. Brun e A. Strugarek. "From stellar coronae to gyrochronology: A theoretical and observational exploration". Astronomy & Astrophysics 635 (março de 2020): A170. http://dx.doi.org/10.1051/0004-6361/201936974.
Texto completo da fonteDeng, Bailin, Sofien Bouaziz, Mario Deuss, Alexandre Kaspar, Yuliy Schwartzburg e Mark Pauly. "Interactive design exploration for constrained meshes". Computer-Aided Design 61 (abril de 2015): 13–23. http://dx.doi.org/10.1016/j.cad.2014.01.004.
Texto completo da fonteYang, Yong-Liang, Yi-Jun Yang, Helmut Pottmann e Niloy J. Mitra. "Shape space exploration of constrained meshes". ACM Transactions on Graphics 30, n.º 6 (dezembro de 2011): 1–12. http://dx.doi.org/10.1145/2070781.2024158.
Texto completo da fonteAngmalisang, Helen Yuliana, Syaiful Anam e Sobri Abusini. "Leaders and followers algorithm for constrained non-linear optimization". Indonesian Journal of Electrical Engineering and Computer Science 13, n.º 1 (1 de janeiro de 2019): 162. http://dx.doi.org/10.11591/ijeecs.v13.i1.pp162-169.
Texto completo da fonteFrancis, Gilad, Lionel Ott, Roman Marchant e Fabio Ramos. "Occupancy map building through Bayesian exploration". International Journal of Robotics Research 38, n.º 7 (6 de maio de 2019): 769–92. http://dx.doi.org/10.1177/0278364919846549.
Texto completo da fonteGupta, Surabhi, e Sudhir Kumar Gupta. "An information theoretic exploration of constrained MSSM". Nuclear Physics B 965 (abril de 2021): 115336. http://dx.doi.org/10.1016/j.nuclphysb.2021.115336.
Texto completo da fonteDwianto, Yohanes Bimo, e Ardanto Mohammad Pramutadi. "Drag Minimization of Low Subsonic Airfoil with Constrained Genetic Algorithm". Mesin 29, n.º 2 (28 de dezembro de 2023): 27–40. http://dx.doi.org/10.5614/mesin.2023.29.2.3.
Texto completo da fonteVallée, Marc A., William A. Morris, Stéphane Perrouty, Robert G. Lee, Ken Wasyliuk, Julia J. King, Kevin Ansdell et al. "Geophysical inversion contributions to mineral exploration: lessons from the Footprints project". Canadian Journal of Earth Sciences 56, n.º 5 (maio de 2019): 525–43. http://dx.doi.org/10.1139/cjes-2019-0009.
Texto completo da fonteSun, Ying, e Yuelin Gao. "An improved composite particle swarm optimization algorithm for solving constrained optimization problems and its engineering applications". AIMS Mathematics 9, n.º 4 (2024): 7917–44. http://dx.doi.org/10.3934/math.2024385.
Texto completo da fonteBacanin, Nebojsa, e Milan Tuba. "Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint". Scientific World Journal 2014 (2014): 1–16. http://dx.doi.org/10.1155/2014/721521.
Texto completo da fonteYang, Jian Chun, e Wen Long. "Improved Grey Wolf Optimization Algorithm for Constrained Mechanical Design Problems". Applied Mechanics and Materials 851 (agosto de 2016): 553–58. http://dx.doi.org/10.4028/www.scientific.net/amm.851.553.
Texto completo da fonteJamgochian, Arec, Anthony Corso e Mykel J. Kochenderfer. "Online Planning for Constrained POMDPs with Continuous Spaces through Dual Ascent". Proceedings of the International Conference on Automated Planning and Scheduling 33, n.º 1 (1 de julho de 2023): 198–202. http://dx.doi.org/10.1609/icaps.v33i1.27195.
Texto completo da fonteZhou, Ding, Zhenhua Yu, Yanquan Zhang e Shunli Li. "Translational and rotational motion planning for spacecraft close proximity using sampling-based methods". Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, n.º 10 (9 de outubro de 2018): 3680–99. http://dx.doi.org/10.1177/0954410018803986.
Texto completo da fonteBairamkulov, Rassul, Kan Xu, Mikhail Popovich, Juan S. Ochoa, Vaishnav Srinivas e Eby G. Friedman. "Power Delivery Exploration Methodology Based on Constrained Optimization". IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 39, n.º 9 (setembro de 2020): 1916–24. http://dx.doi.org/10.1109/tcad.2019.2925397.
Texto completo da fonteYang, Qisong, Thiago D. Simão, Simon H. Tindemans e Matthijs T. J. Spaan. "WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 12 (18 de maio de 2021): 10639–46. http://dx.doi.org/10.1609/aaai.v35i12.17272.
Texto completo da fonteYu, Baosheng, Meng Fang e Dacheng Tao. "Per-Round Knapsack-Constrained Linear Submodular Bandits". Neural Computation 28, n.º 12 (dezembro de 2016): 2757–89. http://dx.doi.org/10.1162/neco_a_00887.
Texto completo da fonteDing, Yuhao, e Javad Lavaei. "Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 6 (26 de junho de 2023): 7396–404. http://dx.doi.org/10.1609/aaai.v37i6.25900.
Texto completo da fonteGarcelon, Evrard, Mohammad Ghavamzadeh, Alessandro Lazaric e Matteo Pirotta. "Improved Algorithms for Conservative Exploration in Bandits". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 3962–69. http://dx.doi.org/10.1609/aaai.v34i04.5812.
Texto completo da fonteSong, Jianping, Hong Ni e Xiaoyong Zhu. "A Distributed Multicast QoS Routing Construction Approach in Information-Centric Networking". Applied Sciences 13, n.º 24 (18 de dezembro de 2023): 13349. http://dx.doi.org/10.3390/app132413349.
Texto completo da fonteBrütting, Jan, Patrick Ole Ohlbrock, Julian Hofer e Pierluigi D’Acunto. "Stock-constrained truss design exploration through combinatorial equilibrium modeling". International Journal of Space Structures 36, n.º 4 (dezembro de 2021): 253–69. http://dx.doi.org/10.1177/09560599211064100.
Texto completo da fonteChung, Jen Jen, Nicholas R. J. Lawrance e Salah Sukkarieh. "Learning to soar: Resource-constrained exploration in reinforcement learning". International Journal of Robotics Research 34, n.º 2 (16 de dezembro de 2014): 158–72. http://dx.doi.org/10.1177/0278364914553683.
Texto completo da fonteSasena, Michael J., Panos Papalambros e Pierre Goovaerts. "Exploration of Metamodeling Sampling Criteria for Constrained Global Optimization". Engineering Optimization 34, n.º 3 (janeiro de 2002): 263–78. http://dx.doi.org/10.1080/03052150211751.
Texto completo da fonteDas, Shantanu, Dariusz Dereniowski e Christina Karousatou. "Collaborative Exploration of Trees by Energy-Constrained Mobile Robots". Theory of Computing Systems 62, n.º 5 (30 de outubro de 2017): 1223–40. http://dx.doi.org/10.1007/s00224-017-9816-3.
Texto completo da fonteChen, Runfeng, Jie Li e Ting Peng. "Decentralized UAV Swarm Scheduling with Constrained Task Exploration Balance". Drones 7, n.º 4 (13 de abril de 2023): 267. http://dx.doi.org/10.3390/drones7040267.
Texto completo da fonteRogers, Andrew, Kasra Eshaghi, Goldie Nejat e Beno Benhabib. "Occupancy Grid Mapping via Resource-Constrained Robotic Swarms: A Collaborative Exploration Strategy". Robotics 12, n.º 3 (9 de maio de 2023): 70. http://dx.doi.org/10.3390/robotics12030070.
Texto completo da fonteGao, Weishang, Cheng Shao e Yi An. "Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization". Mathematical Problems in Engineering 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/762372.
Texto completo da fonteBenavides, Facundo, Caroline Ponzoni Carvalho Chanel, Pablo Monzón e Eduardo Grampín. "An Auto-Adaptive Multi-Objective Strategy for Multi-Robot Exploration of Constrained-Communication Environments". Applied Sciences 9, n.º 3 (9 de fevereiro de 2019): 573. http://dx.doi.org/10.3390/app9030573.
Texto completo da fonteBhattacharjee, Protim, Martin Burger, Anko Borner e Veniamin I. Morgenshtern. "Region-of-Interest Prioritised Sampling for Constrained Autonomous Exploration Systems". IEEE Transactions on Computational Imaging 8 (2022): 302–16. http://dx.doi.org/10.1109/tci.2022.3163552.
Texto completo da fonteMing, Yanbo, Guoqing Ma, Taihan Wang, Bingzhen Ma, Qingfa Meng e Zongrui Li. "Power-Type Structural Self-Constrained Inversion Methods of Gravity and Magnetic Data". Remote Sensing 16, n.º 4 (14 de fevereiro de 2024): 681. http://dx.doi.org/10.3390/rs16040681.
Texto completo da fonteWang, Shengbo, e Ke Li. "Constrained Bayesian Optimization under Partial Observations: Balanced Improvements and Provable Convergence". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 14 (24 de março de 2024): 15607–15. http://dx.doi.org/10.1609/aaai.v38i14.29488.
Texto completo da fonteDing, Zhenhuan, Xiaoge Huang e Zhao Liu. "Active Exploration by Chance-Constrained Optimization for Voltage Regulation with Reinforcement Learning". Energies 15, n.º 2 (16 de janeiro de 2022): 614. http://dx.doi.org/10.3390/en15020614.
Texto completo da fonteYang, Yufei, e Changsheng Zhang. "A Multi-Objective Carnivorous Plant Algorithm for Solving Constrained Multi-Objective Optimization Problems". Biomimetics 8, n.º 2 (26 de março de 2023): 136. http://dx.doi.org/10.3390/biomimetics8020136.
Texto completo da fonteBalakrishnan, Avinash, Djallel Bouneffouf, Nicholas Mattei e Francesca Rossi. "Incorporating Behavioral Constraints in Online AI Systems". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 3–11. http://dx.doi.org/10.1609/aaai.v33i01.33013.
Texto completo da fonteZhou, Manli, Youxi Luo, Guoquan Sun, Guoqin Mai e Fengfeng Zhou. "Constraint Programming Based Biomarker Optimization". BioMed Research International 2015 (2015): 1–5. http://dx.doi.org/10.1155/2015/910515.
Texto completo da fonteLan, Nanying, Fanchang Zhang, Kaipan Xiao, Heng Zhang e Yuhan Lin. "Low-Dimensional Multi-Trace Impedance Inversion in Sparse Space with Elastic Half Norm Constraint". Minerals 13, n.º 7 (22 de julho de 2023): 972. http://dx.doi.org/10.3390/min13070972.
Texto completo da fonteAyton, Benjamin, Brian Williams e Richard Camilli. "Measurement Maximizing Adaptive Sampling with Risk Bounding Functions". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 7511–19. http://dx.doi.org/10.1609/aaai.v33i01.33017511.
Texto completo da fonteDuecker, Daniel Andre, Andreas Rene Geist, Edwin Kreuzer e Eugen Solowjow. "Learning Environmental Field Exploration with Computationally Constrained Underwater Robots: Gaussian Processes Meet Stochastic Optimal Control". Sensors 19, n.º 9 (6 de maio de 2019): 2094. http://dx.doi.org/10.3390/s19092094.
Texto completo da fonteYasojima, Edson Koiti Kudo, Roberto Célio Limão de Oliveira, Otávio Noura Teixeira e Rodrigo Lisbôa Pereira. "CAM-ADX: A New Genetic Algorithm with Increased Intensification and Diversification for Design Optimization Problems with Real Variables". Robotica 37, n.º 9 (1 de março de 2019): 1595–640. http://dx.doi.org/10.1017/s026357471900016x.
Texto completo da fonteMolina, Anton, Shailabh Kumar, Stefan Karpitschka e Manu Prakash. "Droplet tilings for rapid exploration of spatially constrained many-body systems". Proceedings of the National Academy of Sciences 118, n.º 34 (20 de agosto de 2021): e2020014118. http://dx.doi.org/10.1073/pnas.2020014118.
Texto completo da fonteZhao, Zhuoran, Kamyar Mirzazad Barijough e Andreas Gerstlauer. "Network-level Design Space Exploration of Resource-constrained Networks-of-Systems". ACM Transactions on Embedded Computing Systems 19, n.º 4 (16 de julho de 2020): 1–26. http://dx.doi.org/10.1145/3387918.
Texto completo da fonteAdamatzky, Andrew. "On exploration of geometrically constrained space by medicinal leeches Hirudo verbana". Biosystems 130 (abril de 2015): 28–36. http://dx.doi.org/10.1016/j.biosystems.2015.02.005.
Texto completo da fonteAli, M. M., e Z. Kajee-Bagdadi. "A local exploration-based differential evolution algorithm for constrained global optimization". Applied Mathematics and Computation 208, n.º 1 (fevereiro de 2009): 31–48. http://dx.doi.org/10.1016/j.amc.2008.11.036.
Texto completo da fonteRobertson, Scott P., David Koizumi e Stacy C. Marsella. "Constraints on Training: Informativeness and Breadth in Procedural Skill Learning". Proceedings of the Human Factors Society Annual Meeting 32, n.º 5 (outubro de 1988): 377–80. http://dx.doi.org/10.1177/154193128803200532.
Texto completo da fonteCazzato, Dario, Pierluigi Carcagnì, Claudio Cimarelli, Holger Voos, Cosimo Distante e Marco Leo. "Ocular Biometrics Recognition by Analyzing Human Exploration during Video Observations". Applied Sciences 10, n.º 13 (30 de junho de 2020): 4548. http://dx.doi.org/10.3390/app10134548.
Texto completo da fonteBouskela, Adrien, Alexandre Kling, Tristan Schuler, Sergey Shkarayev, Himangshu Kalita e Jekan Thangavelautham. "Mars Exploration Using Sailplanes". Aerospace 9, n.º 6 (3 de junho de 2022): 306. http://dx.doi.org/10.3390/aerospace9060306.
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