Artigos de revistas sobre o tema "Sparsely rewarded environments"
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Dubey, Rachit, Thomas L. Griffiths e Peter Dayan. "The pursuit of happiness: A reinforcement learning perspective on habituation and comparisons". PLOS Computational Biology 18, n.º 8 (4 de agosto de 2022): e1010316. http://dx.doi.org/10.1371/journal.pcbi.1010316.
Texto completo da fonteShi, Xiaoping, Shiqi Zou, Shenmin Song e Rui Guo. "A multi-objective sparse evolutionary framework for large-scale weapon target assignment based on a reward strategy". Journal of Intelligent & Fuzzy Systems 40, n.º 5 (22 de abril de 2021): 10043–61. http://dx.doi.org/10.3233/jifs-202679.
Texto completo da fonteSakamoto, Yuma, e Kentarou Kurashige. "Self-Generating Evaluations for Robot’s Autonomy Based on Sensor Input". Machines 11, n.º 9 (6 de setembro de 2023): 892. http://dx.doi.org/10.3390/machines11090892.
Texto completo da fonteParisi, Simone, Davide Tateo, Maximilian Hensel, Carlo D’Eramo, Jan Peters e Joni Pajarinen. "Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning". Algorithms 15, n.º 3 (28 de fevereiro de 2022): 81. http://dx.doi.org/10.3390/a15030081.
Texto completo da fonteMguni, David, Taher Jafferjee, Jianhong Wang, Nicolas Perez-Nieves, Wenbin Song, Feifei Tong, Matthew Taylor et al. "Learning to Shape Rewards Using a Game of Two Partners". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 10 (26 de junho de 2023): 11604–12. http://dx.doi.org/10.1609/aaai.v37i10.26371.
Texto completo da fonteForbes, Grant C., e David L. Roberts. "Potential-Based Reward Shaping for Intrinsic Motivation (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 21 (24 de março de 2024): 23488–89. http://dx.doi.org/10.1609/aaai.v38i21.30441.
Texto completo da fonteXu, Pei, Junge Zhang, Qiyue Yin, Chao Yu, Yaodong Yang e Kaiqi Huang. "Subspace-Aware Exploration for Sparse-Reward Multi-Agent Tasks". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 10 (26 de junho de 2023): 11717–25. http://dx.doi.org/10.1609/aaai.v37i10.26384.
Texto completo da fonteKubovčík, Martin, Iveta Dirgová Luptáková e Jiří Pospíchal. "Signal Novelty Detection as an Intrinsic Reward for Robotics". Sensors 23, n.º 8 (14 de abril de 2023): 3985. http://dx.doi.org/10.3390/s23083985.
Texto completo da fonteCatacora Ocana, Jim Martin, Roberto Capobianco e Daniele Nardi. "An Overview of Environmental Features that Impact Deep Reinforcement Learning in Sparse-Reward Domains". Journal of Artificial Intelligence Research 76 (26 de abril de 2023): 1181–218. http://dx.doi.org/10.1613/jair.1.14390.
Texto completo da fonteZhou, Xiao, Song Zhou, Xingang Mou e Yi He. "Multirobot Collaborative Pursuit Target Robot by Improved MADDPG". Computational Intelligence and Neuroscience 2022 (25 de fevereiro de 2022): 1–10. http://dx.doi.org/10.1155/2022/4757394.
Texto completo da fonteVelasquez, Alvaro, Brett Bissey, Lior Barak, Andre Beckus, Ismail Alkhouri, Daniel Melcer e George Atia. "Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 13 (18 de maio de 2021): 12015–23. http://dx.doi.org/10.1609/aaai.v35i13.17427.
Texto completo da fonteYan Kong, Yan Kong, Yefeng Rui Yan Kong e Chih-Hsien Hsia Yefeng Rui. "A Deep Reinforcement Learning-Based Approach in Porker Game". 電腦學刊 34, n.º 2 (abril de 2023): 041–51. http://dx.doi.org/10.53106/199115992023043402004.
Texto completo da fonteBougie, Nicolas, e Ryutaro Ichise. "Skill-based curiosity for intrinsically motivated reinforcement learning". Machine Learning 109, n.º 3 (10 de outubro de 2019): 493–512. http://dx.doi.org/10.1007/s10994-019-05845-8.
Texto completo da fonteJiang, Jiechuan, e Zongqing Lu. "Generative Exploration and Exploitation". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 4337–44. http://dx.doi.org/10.1609/aaai.v34i04.5858.
Texto completo da fonteHUANG, XIAO, e JUYANG WENG. "INHERENT VALUE SYSTEMS FOR AUTONOMOUS MENTAL DEVELOPMENT". International Journal of Humanoid Robotics 04, n.º 02 (junho de 2007): 407–33. http://dx.doi.org/10.1142/s0219843607001011.
Texto completo da fonteLi, Yuangang, Tao Guo, Qinghua Li e Xinyue Liu. "Optimized Feature Extraction for Sample Efficient Deep Reinforcement Learning". Electronics 12, n.º 16 (18 de agosto de 2023): 3508. http://dx.doi.org/10.3390/electronics12163508.
Texto completo da fonteTang, Wanxing, Chuang Cheng, Haiping Ai e Li Chen. "Dual-Arm Robot Trajectory Planning Based on Deep Reinforcement Learning under Complex Environment". Micromachines 13, n.º 4 (31 de março de 2022): 564. http://dx.doi.org/10.3390/mi13040564.
Texto completo da fonteShah, Naman, e Siddharth Srivastava. "Hierarchical Planning and Learning for Robots in Stochastic Settings Using Zero-Shot Option Invention". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 9 (24 de março de 2024): 10358–67. http://dx.doi.org/10.1609/aaai.v38i9.28903.
Texto completo da fonteLi, Huale, Rui Cao, Xuan Wang, Xiaohan Hou, Tao Qian, Fengwei Jia, Jiajia Zhang e Shuhan Qi. "AIBPO: Combine the Intrinsic Reward and Auxiliary Task for 3D Strategy Game". Complexity 2021 (13 de julho de 2021): 1–9. http://dx.doi.org/10.1155/2021/6698231.
Texto completo da fonteDharmavaram, Akshay, Matthew Riemer e Shalabh Bhatnagar. "Hierarchical Average Reward Policy Gradient Algorithms (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 10 (3 de abril de 2020): 13777–78. http://dx.doi.org/10.1609/aaai.v34i10.7160.
Texto completo da fonteZhu, Chenyang, Yujie Cai, Jinyu Zhu, Can Hu e Jia Bi. "GR(1)-Guided Deep Reinforcement Learning for Multi-Task Motion Planning under a Stochastic Environment". Electronics 11, n.º 22 (13 de novembro de 2022): 3716. http://dx.doi.org/10.3390/electronics11223716.
Texto completo da fonteRamakrishnan, Santhosh K., Dinesh Jayaraman e Kristen Grauman. "Emergence of exploratory look-around behaviors through active observation completion". Science Robotics 4, n.º 30 (15 de maio de 2019): eaaw6326. http://dx.doi.org/10.1126/scirobotics.aaw6326.
Texto completo da fonteHasanbeig, Mohammadhosein, Natasha Yogananda Jeppu, Alessandro Abate, Tom Melham e Daniel Kroening. "DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 9 (18 de maio de 2021): 7647–56. http://dx.doi.org/10.1609/aaai.v35i9.16935.
Texto completo da fonteHan, Huiyan, Jiaqi Wang, Liqun Kuang, Xie Han e Hongxin Xue. "Improved Robot Path Planning Method Based on Deep Reinforcement Learning". Sensors 23, n.º 12 (15 de junho de 2023): 5622. http://dx.doi.org/10.3390/s23125622.
Texto completo da fonteZhang, Tengteng, e Hongwei Mo. "Research on Perception and Control Technology for Dexterous Robot Operation". Electronics 12, n.º 14 (13 de julho de 2023): 3065. http://dx.doi.org/10.3390/electronics12143065.
Texto completo da fonteNeider, Daniel, Jean-Raphael Gaglione, Ivan Gavran, Ufuk Topcu, Bo Wu e Zhe Xu. "Advice-Guided Reinforcement Learning in a non-Markovian Environment". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 10 (18 de maio de 2021): 9073–80. http://dx.doi.org/10.1609/aaai.v35i10.17096.
Texto completo da fonteZhang, Xiaoping, Yihao Liu, Li Wang, Dunli Hu e Lei Liu. "A Curiosity-Based Autonomous Navigation Algorithm for Maze Robot". Journal of Advanced Computational Intelligence and Intelligent Informatics 26, n.º 6 (20 de novembro de 2022): 893–904. http://dx.doi.org/10.20965/jaciii.2022.p0893.
Texto completo da fonteHan, Ziyao, Fan Yi e Kazuhiro Ohkura. "Collective Transport Behavior in a Robotic Swarm with Hierarchical Imitation Learning". Journal of Robotics and Mechatronics 36, n.º 3 (20 de junho de 2024): 538–45. http://dx.doi.org/10.20965/jrm.2024.p0538.
Texto completo da fonteAbu Bakar, Mohamad Hafiz, Abu Ubaidah Shamsudin, Zubair Adil Soomro, Satoshi Tadokoro e C. J. Salaan. "FUSION SPARSE AND SHAPING REWARD FUNCTION IN SOFT ACTOR-CRITIC DEEP REINFORCEMENT LEARNING FOR MOBILE ROBOT NAVIGATION". Jurnal Teknologi 86, n.º 2 (15 de janeiro de 2024): 37–49. http://dx.doi.org/10.11113/jurnalteknologi.v86.20147.
Texto completo da fonteSharip, Zati, Mohd Hafiz Zulkifli, Mohd Nur Farhan Abd Wahab, Zubaidi Johar e Mohd Zaki Mat Amin. "ASSESSING TROPHIC STATE AND WATER QUALITY OF SMALL LAKES AND PONDS IN PERAK". Jurnal Teknologi 86, n.º 2 (15 de janeiro de 2024): 51–59. http://dx.doi.org/10.11113/jurnalteknologi.v86.20566.
Texto completo da fonteSu, Linfeng, Jinbo Wang e Hongbo Chen. "A Real-Time and Optimal Hypersonic Entry Guidance Method Using Inverse Reinforcement Learning". Aerospace 10, n.º 11 (7 de novembro de 2023): 948. http://dx.doi.org/10.3390/aerospace10110948.
Texto completo da fonteWang, Yifan, e Meibao Yao. "Autonomous Robots Traverse Multi-Terrain Environments via Hierarchical Reinforcement Learning with Skill Discovery". Journal of Physics: Conference Series 2762, n.º 1 (1 de maio de 2024): 012003. http://dx.doi.org/10.1088/1742-6596/2762/1/012003.
Texto completo da fonteZhang, Yilin, Huimin Sun, Honglin Sun, Yuan Huang e Kenji Hashimoto. "Biped Robots Control in Gusty Environments with Adaptive Exploration Based DDPG". Biomimetics 9, n.º 6 (8 de junho de 2024): 346. http://dx.doi.org/10.3390/biomimetics9060346.
Texto completo da fonteSong, Qingpeng, Yuansheng Liu, Ming Lu, Jun Zhang, Han Qi, Ziyu Wang e Zijian Liu. "Autonomous Driving Decision Control Based on Improved Proximal Policy Optimization Algorithm". Applied Sciences 13, n.º 11 (24 de maio de 2023): 6400. http://dx.doi.org/10.3390/app13116400.
Texto completo da fonteKim, MyeongSeop, e Jung-Su Kim. "Policy-based Deep Reinforcement Learning for Sparse Reward Environment". Transactions of The Korean Institute of Electrical Engineers 70, n.º 3 (31 de março de 2021): 506–14. http://dx.doi.org/10.5370/kiee.2021.70.3.506.
Texto completo da fontePotjans, Wiebke, Abigail Morrison e Markus Diesmann. "A Spiking Neural Network Model of an Actor-Critic Learning Agent". Neural Computation 21, n.º 2 (fevereiro de 2009): 301–39. http://dx.doi.org/10.1162/neco.2008.08-07-593.
Texto completo da fonteRauber, Paulo, Avinash Ummadisingu, Filipe Mutz e Jürgen Schmidhuber. "Reinforcement Learning in Sparse-Reward Environments With Hindsight Policy Gradients". Neural Computation 33, n.º 6 (13 de maio de 2021): 1498–553. http://dx.doi.org/10.1162/neco_a_01387.
Texto completo da fonteYu, Sheng, Wei Zhu e Yong Wang. "Research on Wargame Decision-Making Method Based on Multi-Agent Deep Deterministic Policy Gradient". Applied Sciences 13, n.º 7 (4 de abril de 2023): 4569. http://dx.doi.org/10.3390/app13074569.
Texto completo da fonteZhang, Danyang, Zhaolong Xuan, Yang Zhang, Jiangyi Yao, Xi Li e Xiongwei Li. "Path Planning of Unmanned Aerial Vehicle in Complex Environments Based on State-Detection Twin Delayed Deep Deterministic Policy Gradient". Machines 11, n.º 1 (13 de janeiro de 2023): 108. http://dx.doi.org/10.3390/machines11010108.
Texto completo da fonteYao, Jiangyi, Xiongwei Li, Yang Zhang, Jingyu Ji, Yanchao Wang e Yicen Liu. "Path Planning of Unmanned Helicopter in Complex Dynamic Environment Based on State-Coded Deep Q-Network". Symmetry 14, n.º 5 (21 de abril de 2022): 856. http://dx.doi.org/10.3390/sym14050856.
Texto completo da fonteLei, Xiaoyun, Zhian Zhang e Peifang Dong. "Dynamic Path Planning of Unknown Environment Based on Deep Reinforcement Learning". Journal of Robotics 2018 (18 de setembro de 2018): 1–10. http://dx.doi.org/10.1155/2018/5781591.
Texto completo da fonteZhang, Zhizhuo, e Change Zheng. "Simulation of Robotic Arm Grasping Control Based on Proximal Policy Optimization Algorithm". Journal of Physics: Conference Series 2203, n.º 1 (1 de fevereiro de 2022): 012065. http://dx.doi.org/10.1088/1742-6596/2203/1/012065.
Texto completo da fonteLuu, Tung M., e Chang D. Yoo. "Hindsight Goal Ranking on Replay Buffer for Sparse Reward Environment". IEEE Access 9 (2021): 51996–2007. http://dx.doi.org/10.1109/access.2021.3069975.
Texto completo da fonteFeng, Shiying, Xiaofeng Li, Lu Ren e Shuiqing Xu. "Reinforcement learning with parameterized action space and sparse reward for UAV navigation". Intelligence & Robotics 3, n.º 2 (27 de junho de 2023): 161–75. http://dx.doi.org/10.20517/ir.2023.10.
Texto completo da fonteLiu, Zeyang, Lipeng Wan, Xinrui Yang, Zhuoran Chen, Xingyu Chen e Xuguang Lan. "Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 16 (24 de março de 2024): 17487–95. http://dx.doi.org/10.1609/aaai.v38i16.29698.
Texto completo da fonteJiang, Haobin, Ziluo Ding e Zongqing Lu. "Settling Decentralized Multi-Agent Coordinated Exploration by Novelty Sharing". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 16 (24 de março de 2024): 17444–52. http://dx.doi.org/10.1609/aaai.v38i16.29693.
Texto completo da fonteXu, He A., Alireza Modirshanechi, Marco P. Lehmann, Wulfram Gerstner e Michael H. Herzog. "Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making". PLOS Computational Biology 17, n.º 6 (3 de junho de 2021): e1009070. http://dx.doi.org/10.1371/journal.pcbi.1009070.
Texto completo da fonteZeng, Junjie, Rusheng Ju, Long Qin, Yue Hu, Quanjun Yin e Cong Hu. "Navigation in Unknown Dynamic Environments Based on Deep Reinforcement Learning". Sensors 19, n.º 18 (5 de setembro de 2019): 3837. http://dx.doi.org/10.3390/s19183837.
Texto completo da fontePark, Minjae, Chaneun Park e Nam Kyu Kwon. "Autonomous Driving of Mobile Robots in Dynamic Environments Based on Deep Deterministic Policy Gradient: Reward Shaping and Hindsight Experience Replay". Biomimetics 9, n.º 1 (13 de janeiro de 2024): 51. http://dx.doi.org/10.3390/biomimetics9010051.
Texto completo da fonteMourad, Nafee, Ali Ezzeddine, Babak Nadjar Araabi e Majid Nili Ahmadabadi. "Learning from Demonstrations and Human Evaluative Feedbacks: Handling Sparsity and Imperfection Using Inverse Reinforcement Learning Approach". Journal of Robotics 2020 (13 de janeiro de 2020): 1–18. http://dx.doi.org/10.1155/2020/3849309.
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