Suchergebnisse - "multi-agent reinforcement learning algorithm"

Multi-agent deep reinforcement learning-based robotic arm assembly research von Cao, Guohua, Bai, Jimeng

“… in robotic arm assembly processes. To address these issues, this paper proposes a method that employs a multi-agent reinforcement learning algorithm for the shaft-hole assembly of robotic arms, with a specific focus on square shaft-hole assemblies …”
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Transmission Scheduling for Remote State Estimation in CPSs With Two-Hop Networks Subject to DoS Attacks von Xing, Wei, Zhao, Xudong

“… In this paper, a dynamic zero-sum game is formulated to describe the power decision-making process of the sensor/relay and the DoS attacker in cyber-physical …”
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Multi-Agent Reinforcement Learning for Extended Flexible Job Shop Scheduling von Peng, Shaoming, Xiong, Gang, Yang, Jing, Shen, Zhen, Tamir, Tariku Sinshaw, Tao, Zhikun, Han, Yunjun, Wang, Fei-Yue

“… To deal with the above challenges, we propose a multi-agent reinforcement learning algorithm where the scheduling environment is modeled as a decentralized partially observable Markov …”
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计及风电的发电商报价多智能体模型 von 黄飞虎, 李沛东, 彭舰, 董石磊, 赵红磊, 宋卫平, 李强

“… TP389; 新型电力系统背景下,新能源发电商的报价问题一直是电力现货市场中的研究热点.相比传统能源,风电出力受外界不确定性因素的影响较大,给风力发电商求解最优报价带来了 …”
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Distributed Resource Management for Wireless Networks over Unlicensed Spectrum von Han, Mengqi

“… In the past decades, a variety of wireless networks have been deployed, e.g., long term evolution (LTE) cellular networks, wireless local network networks …”
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A Survey on Population-Based Deep Reinforcement Learning von Long, Weifan, Hou, Taixian, Wei, Xiaoyi, Yan, Shichao, Zhai, Peng, Zhang, Lihua

“… We introduce several independent subject areas, including naive self-play, fictitious self-play, population-play, evolution-based training methods, and the policy-space response oracle family …”
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Network-Wide Traffic Signal Control Based on MARL with Hierarchical Nash-Stackelberg Game Model von Shen, Hui, Zhao, Hongxia, Zhang, Zundong, Yang, Xun, Song, Yutong, Liu, Xiaoming

“… The model takes into account traffic control strategies between and within sub-areas of the road network, with important intersections in the two sub-areas as the game subject at the upper layer …”
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Artificial Intelligence Algorithms for Large Economic and Computer Games von Li, Zun

“… Specifically, I study the following subject: how a structured combination of modern artificial intelligence methods facilitates strategic reasoning focusing on equilibrium concepts on multiagent systems of diverse domains, especially …”
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