Search Results - Counterfactual Multi-Agent reinforcement learning algorithm

Multi-agent reinforcement learning vibration control and trajectory planning of a double flexible beam coupling system by 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…”
Get full text

Counterfactual-Based Action Evaluation Algorithm in Multi-Agent Reinforcement Learning by 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…”
Get full text

Energy management based on multi-agent deep reinforcement learning for a multi-energy industrial park by 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…”
Get full text

Distributed Task Migration Optimization in MEC by Extending Multi-Agent Deep Reinforcement Learning Approach by 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…”
Get full text

An Effective Training Method for Counterfactual Multi-Agent Policy Network Based on Differential Evolution Algorithm by 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…”
Get full text

Collaborative Task Offloading Optimization for Satellite Mobile Edge Computing Using Multi-Agent Deep Reinforcement Learning by 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…”
Get full text

Multi-agent deep reinforcement learning for trajectory planning in UAVs-assisted mobile edge computing with heterogeneous requirements by Fan, Chenchen, Xu, Hongyu, Wang, Qingling

“… To address the considered trajectory planning optimization problem, a collaborative multi-agent deep reinforcement learning (MADRL…”
Get full text

Cooperative Multi-Agent Deep Reinforcement Learning with Counterfactual Reward by 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…”
Get full text

Distributed Digital Twin Migration in Multi-Tier Computing Systems by 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…”
Get full text

Counterfactual value decomposition for cooperative multi-agent reinforcement learning by Liu, Kai, Zhang, Tianxian, Xu, Xiangliang, Zhao, Yuyang

“…Value decomposition has become a central focus in Multi-Agent Reinforcement Learning (MARL) in recent years…”
Get full text

Adherence Improves Cooperation in Sequential Social Dilemmas by 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…”
Get full text

Hierarchical Task Offloading for Vehicular Fog Computing Based on Multi-Agent Deep Reinforcement Learning by 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…”
Get full text

DNN Inference Acceleration for Smart Devices in Industry 5.0 by Decentralized Deep Reinforcement Learning by 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…”
Get full text

Counterfactual Multi-Agent Reinforcement Learning for Long- Horizon Medical Assistive Tasks with Dual-arm Robot by 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…”
Get more information

Cooperative traffic signal control through a counterfactual multi-agent deep actor critic approach by 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…”
Get full text

Multi-Agent Reinforcement Learning-Based Digital Twin Migration Over Wireless Networks by 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…”
Get full text

Counterfactual Reward Estimation for Credit Assignment in Multi-agent Deep Reinforcement Learning over Wireless Video Transmission by 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…”
Get full text

Cooperative and Competitive Multi-Agent Systems: From Optimization to Games by 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…”
Get full text

Cross-Regional Task Offloading with Multi-Agent Reinforcement Learning for Hierarchical Vehicular Fog Computing by 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…”
Get full text

Joint Optimization of Handover Control and Power Allocation Based on Multi-Agent Deep Reinforcement Learning by 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…”
Get full text