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Björn Lindenberg, Jonas Nordqvist and Karl-Olof Lindahl
It is well known that ensemble methods often provide enhanced performance in reinforcement learning. In this paper, we explore this concept further by using group-aided training within the distributional reinforcement learning paradigm. Specifically, we ...
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Juyao Wei, Zhenggang Lu, Zheng Yin and Zhipeng Jing
This paper presents a novel data-driven multiagent reinforcement learning (MARL) controller for enhancing the running stability of independently rotating wheels (IRW) and reducing wheel?rail wear. We base our active guidance controller on the multiagent ...
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Jishu K. Medhi, Rui Liu, Qianlong Wang and Xuhui Chen
Multiple unmanned aerial vehicle (multi-UAV) systems have gained significant attention in applications, such as aerial surveillance and search and rescue missions. With the recent development of state-of-the-art multiagent reinforcement learning (MARL) a...
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Giuseppe Vizzari and Thomas Cecconello
Pedestrian simulation is a consolidated but still lively area of research. State of the art models mostly take an agent-based perspective, in which pedestrian decisions are made according to a manually defined model. Reinforcement learning (RL), on the o...
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Qianqian Wu, Qiang Liu, Zefan Wu and Jiye Zhang
In the field of ocean data monitoring, collaborative control and path planning of unmanned aerial vehicles (UAVs) are essential for improving data collection efficiency and quality. In this study, we focus on how to utilize multiple UAVs to efficiently c...
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Xiangdong Tang, Fei Chen and Yunlong He
Video viewing is currently the primary form of entertainment for modern people due to the rapid development of mobile devices and 5G networks. The combination of pervasive edge devices and adaptive bitrate streaming technologies can lessen the effects of...
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Huimu Wang, Zhen Liu, Jianqiang Yi and Zhiqiang Pu
Multiagent cooperation is one of the most attractive research fields in multiagent systems. There are many attempts made by researchers in this field to promote cooperation behavior. However, several issues still exist, such as complex interactions among...
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Yu-Juan Luo, Cheng-Lin Liu and Guang-Ye Liu
This paper deals with the consensus tracking problem of heterogeneous linear multiagent systems under the repeatable operation environment, and adopts a proportional differential (PD)-type iterative learning control (ILC) algorithm based on the fractiona...
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