Suchergebnisse - "PARTIALLY observable Markov decision processes"

Optimal Replacement for a Partially Observable System Subject to Dependent Failure Modes.

Autoren: Zheng, Rui¹ (AUTHOR) rui_zheng@hfut.edu.cn

Quelle: Naval Research Logistics. Oct2025, p1. 13p. 12 Illustrations.

Schlagwörter: *QUALITY control charts, CONDITION-based maintenance, PARTIALLY observable Markov decision processes, STOCHASTIC systems, DETERIORATION of materials, FAILURE mode & effects analysis, SYSTEM failures

Optimal Abort Policy for Mission-Critical Systems Under Imperfect Condition Monitoring.

Autoren: Sun, Qiuzhuang Hu, Jiawen Ye, Zhi-Sheng

Quelle: Operations Research. Sep/Oct2025, Vol. 73 Issue 5, p2396-2416. 21p.

Schlagwörter: *MARKOV processes, *FAULT tolerance (Engineering), *FAILURE analysis, *STOCHASTIC processes, *DECISION making, PARTIALLY observable Markov decision processes, DRONE aircraft

Mission Abort Policy Considering Imperfect Alarms and Two Abort Options.

Autoren: Hu, Jiawen Chen, Piao

Quelle: Naval Research Logistics. Sep2025, Vol. 72 Issue 6, p858-867. 10p.

Schlagwörter: *DECISION making, *FAULT tolerance (Engineering), PARTIALLY observable Markov decision processes, FALSE alarms, DRONE aircraft

Semi‐Markovian planning to coordinate aerial and maritime medical evacuation platforms.

Autoren: Al‐Husseini, Mahdi Wray, Kyle H. Kochenderfer, Mykel J.

Quelle: AI Magazine. Sep2025, Vol. 46 Issue 3, p1-14. 14p.

Schlagwörter: *EMERGENCY management, *AIR travel, *HEURISTIC, TRANSPORTATION of patients, PARTIALLY observable Markov decision processes, CIVILIAN evacuation, MARITIME management

Firma/Körperschaft: UNITED States. Army

Learning to Balance the Performance and Deterioration of Aging Systems Through Derating.

Autoren: Wang, Jue¹ (AUTHOR) juewang-faculty@queensu.ca

Quelle: Production & Operations Management. Jul2025, Vol. 34 Issue 7, p1743-1758. 16p.

Schlagwörter: PARTIALLY observable Markov decision processes, CONDITION-based maintenance

Miss-Triggered Content Cache Replacement Under Partial Observability: Transformer-Decoder Q-Learning.

Autoren: Kim, Hakho Sun, Teh-Jen Huh, Eui-Nam

Quelle: Mathematics (2227-7390). Oct2025, Vol. 13 Issue 19, p3217. 27p.

Schlagwörter: *REINFORCEMENT learning, *PARTIALLY observable Markov decision processes, *CACHE memory, *CONTENT delivery networks

Distributionally Robust Partially Observable Markov Decision Process with Distance-Based Ambiguity Sets.

Autoren: Li, Tong Xiang, Yisha

Quelle: IISE Transactions. May2025, p1-16. 16p. 4 Illustrations.

Schlagwörter: *DECISION making, *HEURISTIC, *QUANTITATIVE research, PARTIALLY observable Markov decision processes, ROBUST statistics, CONVEX functions

DRL-Based Scheduling for AoI Minimization in CR Networks with Perfect Sensing.

Autoren: Sun, Juan Zhang, Shubin Yu, Xinjie

Quelle: Entropy. Aug2025, Vol. 27 Issue 8, p855. 24p.

Schlagwörter: *COGNITIVE radio, *PARTIALLY observable Markov decision processes, *SCHEDULING, *REINFORCEMENT learning, *ENERGY harvesting, *DYNAMIC programming, *INTERNET of things

A novel deep reinforcement learning for POMDP-based autonomous ship collision decision-making.

Autoren: Zhang, Xinyu Zheng, Kangjie Wang, Chengbo et al.

Quelle: Neural Computing & Applications. Jul2025, Vol. 37 Issue 21, p15963-15977. 15p.

Schlagwörter: *REINFORCEMENT learning, *PARTIALLY observable Markov decision processes, *REWARD (Psychology), *SIMULATION software, *BOATS & boating, *MARITIME safety, *DECISION making

SP-POMDP: 堆叠物体抓取场景中的任务规划方法.

Alternate Title: SP-POMDP: task planning method for stacked objects grasping scene.

Autoren: 陈奕好 刘金鑫 库涛 et al.

Quelle: Application Research of Computers / Jisuanji Yingyong Yanjiu. Jul2025, Vol. 42 Issue 7, p2064-2071. 8p.

Schlagwörter: *PARTIALLY observable Markov decision processes, *ROBOTS

An Efficient Multi-Agent Policy Self-Play Learning Method Aiming at Seize-Control Scenarios.

Autoren: Zhang, Huaqing Ma, Hongbin Zhang, Xiaofei et al.

Quelle: Unmanned Systems. Jul2025, Vol. 13 Issue 4, p987-1004. 18p.

Schlagwörter: *PARTIALLY observable Markov decision processes, *ARTIFICIAL neural networks, *DEEP reinforcement learning, *LONG short-term memory, *REWARD (Psychology), *REINFORCEMENT learning

An end-to-end decentralised scheduling framework based on deep reinforcement learning for dynamic distributed heterogeneous flowshop scheduling.

Autoren: Li, Haoran Gao, Liang Fan, Qingsong et al.

Quelle: International Journal of Production Research; Jun2025, Vol. 63 Issue 12, p4368-4388, 21p

Schlagwörter: REINFORCEMENT learning, DEEP reinforcement learning, PARTIALLY observable Markov decision processes, FEATURE extraction, AUTODIDACTICISM

Maintenance optimization for multi-component systems with a single sensor.

Autoren: Eggertsson, Ragnar Eruguz, Ayse Sena Basten, Rob et al.

Quelle: European Journal of Operational Research. Feb2025, Vol. 320 Issue 3, p559-569. 11p.

Schlagwörter: *MATHEMATICAL optimization, *INFORMATION storage & retrieval systems, PARTIALLY observable Markov decision processes, STOCHASTIC orders, CONDITION-based maintenance

No compromise in solution quality: Speeding up belief-dependent continuous partially observable Markov decision processes via adaptive multilevel simplification.

Autoren: Zhitnikov, Andrey Sztyglic, Ori Indelman, Vadim

Quelle: International Journal of Robotics Research. Feb2025, Vol. 44 Issue 2, p157-195. 39p.

Schlagwörter: *PRODUCTION planning, *ALGORITHMS, PARTIALLY observable Markov decision processes

Model‐based offline reinforcement learning for sustainable fishery management.

Autoren: Ju, Jun Kurniawati, Hanna Kroese, Dirk et al.

Quelle: Expert Systems. Jan2025, Vol. 42 Issue 1, p1-28. 28p.

Schlagwörter: PARTIALLY observable Markov decision processes, SUSTAINABLE fisheries, FISHERY policy, STOCHASTIC systems, REINFORCEMENT learning

Integrated Energy Optimization in Manufacturing Through Multiagent Deep Reinforcement Learning: Holistic Control of Manufacturing, Microgrid Systems, and Battery Storage.

Autoren: Waseem, Muhammad Maithripala, Mihitha Sarinda Qing Chang et al.

Quelle: Journal of Manufacturing Science & Engineering. Jun2025, Vol. 147 Issue 6, p1-14. 14p.

Schlagwörter: *PARTIALLY observable Markov decision processes, *DEEP reinforcement learning, *SUSTAINABILITY, *REINFORCEMENT learning, *RENEWABLE energy sources

Valuing Imperfect Information from Inspection and Sensing in Condition-Based Roadway Pavement Management with Partially Observable Conditions.

Autoren: Zhou, Weiwen Miller-Hooks, Elise Papakonstantinou, Konstantinos G. et al.

Quelle: Journal of Transportation Engineering. Part B. Pavements. Jun2025, Vol. 151 Issue 2, p1-15. 15p.

Schlagwörter: *PARTIALLY observable Markov decision processes, *DEEP reinforcement learning, *REINFORCEMENT learning, *PAVEMENT management, *PAVEMENTS

Energy Management for Distributed Carbon-Neutral Data Centers †.

Autoren: Chang, Wenting Liu, Chuyi Ren, Guanyu et al.

Quelle: Energies (19961073). Jun2025, Vol. 18 Issue 11, p2861. 20p.

Schlagwörter: *PARTIALLY observable Markov decision processes, *CARBON sequestration, *CARBON emissions, *GREENHOUSE gas mitigation, *POWER resources, *SERVER farms (Computer network management), *CARBON offsetting

Assisted-Value Factorization with Latent Interaction in Cooperate Multi-Agent Reinforcement Learning.

Autoren: Zhao, Zhitong Zhang, Ya Wang, Siying et al.

Quelle: Mathematics (2227-7390). May2025, Vol. 13 Issue 9, p1429. 21p.

Schlagwörter: *PARTIALLY observable Markov decision processes, *GROUP decision making, *DECOMPOSITION method, *MARL

Triple equivalence for the emergence of biological intelligence.

Autoren: Isomura, Takuya¹ (AUTHOR) takuya.isomura@riken.jp

Quelle: Communications Physics. 4/15/2025, Vol. 8 Issue 1, p1-14. 14p.

Schlagwörter: *PARTIALLY observable Markov decision processes, *TURING machines, *HELMHOLTZ free energy, *MATHEMATICAL analysis, *MATHEMATICAL statistics