Suchergebnisse - Counterfactual Multi-Agent reinforcement learning algorithm

Multi-agent reinforcement learning vibration control and trajectory planning of a double flexible beam coupling system von Qiu, Zhi-cheng, Hu, Jun-fei, Zhang, Xian-min

“… A multi-agent reinforcement learning vibration controller is designed for active vibration suppression of a movable double piezoelectric flexible beam coupling system, and the motion trajectory …”
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Counterfactual-Based Action Evaluation Algorithm in Multi-Agent Reinforcement Learning von Yuan, Yuyu, Zhao, Pengqian, Guo, Ting, Jiang, Hongpu

“… for establishing cooperation. Therefore, we propose a novel counterfactual reasoning-based multi-agent reinforcement learning algorithm to evaluate the continuous contribution of agent actions on the latent state …”
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Energy management based on multi-agent deep reinforcement learning for a multi-energy industrial park von Zhu, Dafeng, Yang, Bo, Liu, Yuxiang, Wang, Zhaojian, Ma, Kai, Guan, Xinping

“… Owing to large industrial energy consumption, industrial production has brought a huge burden to the grid in terms of renewable energy access and power supply …”
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Distributed Task Migration Optimization in MEC by Extending Multi-Agent Deep Reinforcement Learning Approach von Liu, Chubo, Tang, Fan, Hu, Yikun, Li, Kenli, Tang, Zhuo, Li, Keqin

“… Closer to mobile users geographically, mobile edge computing (MEC) can provide some cloud-like capabilities to users more efficiently. This enables it possible …”
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An Effective Training Method for Counterfactual Multi-Agent Policy Network Based on Differential Evolution Algorithm von Qu, Shaochun, Guo, Ruiqi, Cao, Zijian, Liu, Jiawei, Su, Baolong, Liu, Minghao

“… ’ policies, counterfactual multi-agent (COMA) stands out in most multi-agent reinforcement learning (MARL) algorithms …”
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Collaborative Task Offloading Optimization for Satellite Mobile Edge Computing Using Multi-Agent Deep Reinforcement Learning von Zhang, Hangyu, Zhao, Hongbo, Liu, Rongke, Kaushik, Aryan, Gao, Xiangqiang, Xu, Shenzhan

“… Furthermore, for evaluating the behavioral contribution of an agent to task completion, we adopt a deep reinforcement learning algorithm based on counterfactual multi-agent policy gradients (COMA …”
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Multi-agent deep reinforcement learning for trajectory planning in UAVs-assisted mobile edge computing with heterogeneous requirements von Fan, Chenchen, Xu, Hongyu, Wang, Qingling

“… To address the considered trajectory planning optimization problem, a collaborative multi-agent deep reinforcement learning (MADRL …”
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Cooperative Multi-Agent Deep Reinforcement Learning with Counterfactual Reward von Shao, Kun, Zhu, Yuanheng, Tang, Zhentao, Zhao, Dongbin

“… To address this credit assignment problem, we propose a multi-agent reinforcement learning algorithm with counterfactual reward mechanism, which is termed as CoRe algorithm …”
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Distributed Digital Twin Migration in Multi-Tier Computing Systems von Chen, Zhixiong, Yi, Wenqiang, Nallanathan, Arumugam, Chambers, Jonathon A.

“… At the network edges, the multi-tier computing framework provides mobile users with efficient cloud-like computing and signal processing capabilities …”
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Counterfactual value decomposition for cooperative multi-agent reinforcement learning von Liu, Kai, Zhang, Tianxian, Xu, Xiangliang, Zhao, Yuyang

“… Value decomposition has become a central focus in Multi-Agent Reinforcement Learning (MARL) in recent years …”
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Adherence Improves Cooperation in Sequential Social Dilemmas von Yuan, Yuyu, Guo, Ting, Zhao, Pengqian, Jiang, Hongpu

“… In recent research, these options to cooperate or defect were temporally extended. Here, we propose a novel adherence-based multi-agent reinforcement learning algorithm …”
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Hierarchical Task Offloading for Vehicular Fog Computing Based on Multi-Agent Deep Reinforcement Learning von Hou, Yukai, Wei, Zhiwei, Zhang, Rongqing, Cheng, Xiang, Yang, Liuqing

“… Vehicular fog computing (VFC) has been expected as a promising architecture that can make full use of computing resources of idle vehicles to increase …”
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DNN Inference Acceleration for Smart Devices in Industry 5.0 by Decentralized Deep Reinforcement Learning von Dong, Chongwu, Shafiq, Muhammad, Dabel, Maryam M. Al, Sun, Yanbin, Tian, Zhihong

“… With the emergence of Industry 5.0, there has been a significant surge in the need for intelligent services within the realm of smart devices. Currently, deep …”
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Counterfactual Multi-Agent Reinforcement Learning for Long- Horizon Medical Assistive Tasks with Dual-arm Robot von Lee, Jin Hyuk, Oh, Ji-Heon, Espinoza, Ismael, Jung, Danbi, Choi, Yong-Hyeok, Lee, Won Hee, Kim, Wonha, Kim, Tae-Seong

“… This study introduces a novel multi-agent reinforcement learning approach, termed Counterfactual Multi-Agent Demo Augmented Policy Gradient (COMA-DAPG …”
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Cooperative traffic signal control through a counterfactual multi-agent deep actor critic approach von Song, Xiang (Ben), Zhou, Bin, Ma, Dongfang

“… In recent years, reinforcement learning (RL) algorithms have attracted the increasing attention of researchers in the area of signal control optimization, since they can learn the optimal timing policy themselves by analyzing changing patterns …”
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Multi-Agent Reinforcement Learning-Based Digital Twin Migration Over Wireless Networks von Chen, Zhixiong, Yi, Wenqiang, Nallanathan, Arumugam

“… To reduce the synchronization latency in digital twin (DT)-enabled wireless edge networks, the DT migration provides an efficient roaming solution among edge …”
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Counterfactual Reward Estimation for Credit Assignment in Multi-agent Deep Reinforcement Learning over Wireless Video Transmission von Wenhan, Y., Qian, Liangxin, Chua, Terence Jie, Zhao, Jun

“… , and enhancing the user experience by addressing successive frame losses. To handle credit assignment in multi-agent scenarios, we integrate counterfactual reward shaping …”
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Cooperative and Competitive Multi-Agent Systems: From Optimization to Games von Wang, Jianrui, Hong, Yitian, Wang, Jiali, Xu, Jiapeng, Tang, Yang, Han, Qing-Long, Kurths, Jurgen

“… Multi-agent systems can solve scientific issues related to complex systems that are difficult or impossible for a single agent to solve through mutual collaboration and cooperation optimization …”
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Cross-Regional Task Offloading with Multi-Agent Reinforcement Learning for Hierarchical Vehicular Fog Computing von Hou, Yukai, Wei, Zhiwei, Liu, Shiyang, Li, Bing, Zhang, Rongqing, Cheng, Xiang, Yang, Liuqing

“… on multi-agent reinforcement learning. Moreover, to tackle the inefficiency caused by the multi-agent credit assignment problem, we provide …”
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Joint Optimization of Handover Control and Power Allocation Based on Multi-Agent Deep Reinforcement Learning von Guo, Delin, Tang, Lan, Zhang, Xinggan, Liang, Ying-Chang

“… , UEs, have the same target. Then, to solve the multi-agent task, and get decentralized policies for each UE, we develop a multi-agent reinforcement learning (MARL …”
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