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