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Shui Jiang, Yanning Ge, Xu Yang, Wencheng Yang and Hui Cui
Reinforcement learning (RL) is pivotal in empowering Unmanned Aerial Vehicles (UAVs) to navigate and make decisions efficiently and intelligently within complex and dynamic surroundings. Despite its significance, RL is hampered by inherent limitations su...
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Tamás Kegyes, Alex Kummer, Zoltán Süle and János Abonyi
We analyzed a special class of graph traversal problems, where the distances are stochastic, and the agent is restricted to take a limited range in one go. We showed that both constrained shortest Hamiltonian pathfinding problems and disassembly line bal...
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Ziyi Wang, Xinran Li, Luoyang Sun, Haifeng Zhang, Hualin Liu and Jun Wang
Efficient yet sufficient exploration remains a critical challenge in reinforcement learning (RL), especially for Markov Decision Processes (MDPs) with vast action spaces. Previous approaches have commonly involved projecting the original action space int...
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Muhammad Sheraz, Teong Chee Chuah, Mardeni Bin Roslee, Manzoor Ahmed, Amjad Iqbal and Ala?a Al-Habashna
Data caching is a promising technique to alleviate the data traffic burden from the backhaul and minimize data access delay. However, the cache capacity constraint poses a significant challenge to obtaining content through the cache resource that degrade...
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Arun Kumar Sangaiah, Amir Javadpour, Chung-Chian Hsu, Anandakumar Haldorai and Ahmad Zeynivand
Vehicular Ad Hoc Network (VANETs) need methods to control traffic caused by a high volume of traffic during day and night, the interaction of vehicles, and pedestrians, vehicle collisions, increasing travel delays, and energy issues. Routing is one of th...
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Siyuan Yang, Mondher Bouazizi, Tomoaki Ohtsuki, Yohei Shibata, Wataru Takabatake, Kenji Hoshino and Atsushi Nagate
In this paper, we propose a novel Deep Reinforcement Learning Evolution Algorithm (DRLEA) method to control the antenna parameters of the High-Altitude Platform Station (HAPS) mobile to reduce the number of low-throughput users. Considering the random mo...
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Nan Ma, Ziyi Wang, Zeyu Ba, Xinran Li, Ning Yang, Xinyi Yang and Haifeng Zhang
Crude oil resource scheduling is one of the critical issues upstream in the crude oil industry chain. It aims to reduce transportation and inventory costs and avoid alerts of inventory limit violations by formulating reasonable crude oil transportation a...
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Fengyuan Yin, Xiaoming Yuan, Zhiao Ma and Xinyu Xu
Permanent magnet synchronous motor (PMSM) drive systems are commonly utilized in mobile electric drive systems due to their high efficiency, high power density, and low maintenance cost. To reduce the tracking error of the permanent magnet synchronous mo...
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Wenting Li, Xiuhui Zhang, Yunfeng Dong, Yan Lin and Hongjue Li
Multi-stage launch vehicles are currently the primary tool for humans to reach extraterrestrial space. The technology of recovering and reusing rockets can effectively shorten rocket launch cycles and reduce space launch costs. With the development of de...
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Raphael C. Engelhardt, Marc Oedingen, Moritz Lange, Laurenz Wiskott and Wolfgang Konen
The demand for explainable and transparent models increases with the continued success of reinforcement learning. In this article, we explore the potential of generating shallow decision trees (DTs) as simple and transparent surrogate models for opaque d...
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