Výsledky vyhľadávania - Counterfactual Multi-Agent reinforcement learning algorithm

Counterfactual value decomposition for cooperative multi-agent reinforcement learning.

Autori: Liu K Zhang T Xu X a ďalší

Zdroj: Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2025 Oct; Vol. 190, pp. 107692. Date of Electronic Publication: 2025 Jun 16.

Spôsob vydávania: Journal Article

Informácie o časopise: Publisher: Pergamon Press Country of Publication: United States NLM ID: 8805018 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-2782 (Electronic) Linking ISSN: 08936080 NLM ISO Abbreviation: Neural Netw Subsets: MEDLINE

Výrazy zo slovníka MeSH: Reinforcement, Psychology* , Neural Networks, Computer* , Cooperative Behavior*, Humans ; Algorithms

Counterfactual Multi-Agent Reinforcement Learning for Long- Horizon Medical Assistive Tasks with Dual-arm Robot.

Autori: Lee JH Oh JH Espinoza I a ďalší

Zdroj: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2025 Jul; Vol. 2025, pp. 1-6.

Spôsob vydávania: Journal Article

Informácie o časopise: Publisher: [IEEE] Country of Publication: United States NLM ID: 101763872 Publication Model: Print Cited Medium: Internet ISSN: 2694-0604 (Electronic) Linking ISSN: 23757477 NLM ISO Abbreviation: Annu Int Conf IEEE Eng Med Biol Soc Subsets: MEDLINE

Výrazy zo slovníka MeSH: Robotics*/instrumentation , Robotics*/methods , Machine Learning* , Self-Help Devices*, Humans ; Algorithms

Counterfactual-Based Action Evaluation Algorithm in Multi-Agent Reinforcement Learning

Autori: Yuyu Yuan Pengqian Zhao Ting Guo a ďalší

Zdroj: Applied Sciences, Vol 12, Iss 7, p 3439 (2022)

Predmety: multi-agent reinforcement learning, multi-agent system, counterfactual reasoning, intrinsic reward, social dilemmas, actor-critic, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2076-3417/12/7/3439; https://doaj.org/toc/2076-3417

Prístupová URL adresa: https://doaj.org/article/7bcee224d1f844d688ab33287ff4bb1d

Counterfactual-Based Action Evaluation Algorithm in Multi-Agent Reinforcement Learning.

Autori: Yuan, Yuyu Zhao, Pengqian Guo, Ting a ďalší

Zdroj: Applied Sciences (2076-3417); Apr2022, Vol. 12 Issue 7, p3439-3439, 14p

Predmety: REINFORCEMENT learning, ALGORITHMS, MACHINE learning

Cooperative Multi-Agent Deep Reinforcement Learning with Counterfactual Reward

Autori: Kun Shao Zhentao Tang Yuanheng Zhu a ďalší

Zdroj: 2020 International Joint Conference on Neural Networks (IJCNN). :1-8

Predmety: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences

Prístupová URL adresa: https://ieeexplore.ieee.org/document/9207169
https://dblp.uni-trier.de/db/conf/ijcnn/ijcnn2020.html#ShaoZTZ20

A New Reinforcement Learning Algorithm Based on Counterfactual Experience Replay

Autori: Gao Wei Chen Jing Li Menglin a ďalší

Zdroj: 2020 39th Chinese Control Conference (CCC). :1994-2001

Predmety: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

Prístupová URL adresa: https://ieeexplore.ieee.org/abstract/document/9189606/

Evolutionary reinforcement learning algorithm for large-scale multi-agent cooperation and confrontation applications.

Autori: Liu, Haiying Li, ZhiHao Huang, Kuihua a ďalší

Zdroj: Journal of Supercomputing; Jan2024, Vol. 80 Issue 2, p2319-2346, 28p

Predmety: MACHINE learning, EVOLUTIONARY algorithms, REINFORCEMENT learning, REWARD (Psychology), DRONE aircraft, COOPERATION

Paving the Way towards Self-adaptive AI Agents: Reinforcement Learning, World Models and Multi-agent Systems

Autori: Wang, Hang

Predmety: Computer science, Robotics, Artificial intelligence, AI Agent, Domain Adaptation, Embodied AI, Multi-agent Networks, Reinforcement Learning, World Model

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/7dx2c9px
https://escholarship.org/content/qt7dx2c9px/qt7dx2c9px.pdf

Multi agent reinforcement learning for online layout planning and scheduling in flexible assembly systems.

Autori: Kaven, Lea Huke, Philipp Göppert, Amon a ďalší

Zdroj: Journal of Intelligent Manufacturing; Dec2024, Vol. 35 Issue 8, p3917-3936, 20p

Predmety: DEEP reinforcement learning, FLEXIBLE manufacturing systems, MACHINE learning, PRODUCTION control, PRODUCTION scheduling

Multiple unmanned surface vehicles pursuit method based on adversarial evolutionary reinforcement learning. (English)

Autori: YAO, Peng HAN, Meiyu WANG, Dechuan a ďalší

Zdroj: Systems Engineering & Electronics; Sep2025, Vol. 47 Issue 9, p2960-2970, 11p

Predmety: LONG short-term memory, MACHINE learning, AUTONOMOUS vehicles, REEFS, ALGORITHMS

Improved representations for cooperative multi-agent reinforcement learning

Autori: Castellini, Jacopo

Prístupová URL adresa: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.863656

Multi-agent reinforcement learning vibration control and trajectory planning of a double flexible beam coupling system.

Autori: Qiu, Zhi-cheng Hu, Jun-fei Zhang, Xian-min

Zdroj: Mechanical Systems & Signal Processing. Oct2023, Vol. 200, pN.PAG-N.PAG. 1p.

Predmety: *OPTIMIZATION algorithms, *TABU search algorithm, *REINFORCEMENT learning, *PIEZOELECTRIC actuators, *TRANSLATIONAL motion, *MACHINE learning, *FINITE element method

Policy Optimization Algorithm with Activation Likelihood-Ratio for Multi-agent Reinforcement Learning.

Autori: Jia, Lu Su, Binglin Xu, Du a ďalší

Zdroj: Neural Processing Letters; Dec2024, Vol. 56 Issue 6, p1-27, 27p

多智能体强化学习算法研究综述. (Chinese)

Alternate Title: Review of Research on Multi-agent Reinforcement Learning Algorithms. (English)

Autori: 李明阳 许可儿 宋志强 a ďalší

Zdroj: Journal of Frontiers of Computer Science & Technology; Aug2024, Vol. 18 Issue 8, p1979-1997, 19p

Advancing Reinforcement Learning: Multi-Agent Optimization, Opportunistic Exploration, and Causal Interpretation

Autori: Wang, Xiaoxiao

Predmety: African literature, Computer science, Electrical engineering, causal explanation, contextual bandit, multi-task learning, opportunistic learning, reinforcement learning

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/88h744ps
https://escholarship.org/content/qt88h744ps/qt88h744ps.pdf

Energy Management Based on Multi-Agent Deep Reinforcement Learning for A Multi-Energy Industrial Park

Autori: Zhu, Dafeng Yang, Bo Liu, Yuxiang a ďalší

Témy: Electrical Engineering and Systems Science - Systems and Control, text

URL: http://arxiv.org/abs/2202.03771

DMADRL: A Distributed Multi-agent Deep Reinforcement Learning Algorithm for Cognitive Offloading in Dynamic MEC Networks.

Autori: Yi, Meng Yang, Peng Du, Miao a ďalší

Zdroj: Neural Processing Letters; Oct2022, Vol. 54 Issue 5, p4341-4373, 33p

Predmety: REINFORCEMENT learning, DISTRIBUTED algorithms, DEEP learning, MACHINE learning, COGNITIVE learning, MARKOV processes, DATA transmission systems

Transform networks for cooperative multi-agent deep reinforcement learning.

Autori: Wang, Hongbin Xie, Xiaodong Zhou, Lianke

Zdroj: Applied Intelligence; Apr2023, Vol. 53 Issue 8, p9261-9269, 9p

Predmety: REINFORCEMENT learning, DEEP learning, MACHINE learning, MONOTONIC functions

Extensible Hierarchical Multi-Agent Reinforcement-Learning Algorithm in Traffic Signal Control.

Autori: Zhao, Pengqian Yuan, Yuyu Guo, Ting

Zdroj: Applied Sciences (2076-3417); Dec2022, Vol. 12 Issue 24, p12783, 14p

Predmety: TRAFFIC signs & signals, TRAFFIC engineering, ALGORITHMS, PROBLEM solving, DECISION making

Distributed Task Migration Optimization in MEC by Extending Multi-Agent Deep Reinforcement Learning Approach

Autori: Chubo Liu Fan Tang Yikun Hu a ďalší

Zdroj: IEEE Transactions on Parallel and Distributed Systems. 32:1603-1614

Predmety: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Prístupová URL adresa: https://dblp.uni-trier.de/db/journals/tpds/tpds32.html#LiuTHLTL21
https://ieeexplore.ieee.org/document/9305956