Results 21 to 30 of about 5,156,964 (309)
Frame Size Optimization for Dynamic Framed Slotted ALOHA in RFID Systems
Jisuanji kexue yu tansuo, 2021 In recent years, the State Grid has actively promoted the construction of ubiquitous power Internet of things, so as to realize the interconnection and optimized management of things in the power system. Specifically, radio frequency identification (RFID)
HE Jindong, BU Yanling, SHI Congcong, XIE Lei
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, 2020 Reinforcement Learning allows us to acquire knowledge without any training data. However, for learning it takes time. In this work, we propose a method to perform Reverse action by using Retrospective Kalman Filter that estimates the state one step before. We show an experience by a Hunter Prey problem. And discuss the usefulness of our proposed method.
Kei Takahata, Takao Miura
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Cybernetics and Information Technologies, 2023 Fog computing is one of the emerging forms of cloud computing which aims to satisfy the ever-increasing computation demands of the mobile applications. Effective offloading of tasks leads to increased efficiency of the fog network, but at the same time ...
Bhargavi K. +2 more
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CoRR, 2023 In Reinforcement Learning the Q-learning algorithm provably converges to the optimal solution. However, as others have demonstrated, Q-learning can also overestimate the values and thereby spend too long exploring unhelpful states. Double Q-learning is a provably convergent alternative that mitigates some of the overestimation issues, though sometimes ...
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Applied Sciences, 2019 Programming robots for performing different activities requires calculating sequences of values of their joints by taking into account many factors, such as stability and efficiency, at the same time. Particularly for walking, state of the art techniques
Cristyan R. Gil +2 more
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Traffic Light Cycle Configuration of Single Intersection Based on Modified Q-Learning
Applied Sciences, 2019 In recent years, within large cities with a high population density, traffic congestion has become more and more serious, resulting in increased emissions of vehicles and reducing the efficiency of urban operations.
Hung-Chi Chu +3 more
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Aircraft Maintenance Check Scheduling Using Reinforcement Learning
Aerospace, 2021 This paper presents a Reinforcement Learning (RL) approach to optimize the long-term scheduling of maintenance for an aircraft fleet. The problem considers fleet status, maintenance capacity, and other maintenance constraints to schedule hangar checks ...
Pedro Andrade +3 more
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Impacto de constantes en algoritmo q-learning en pac-man
, 2022 Se analiza el impacto de variables en la función de q-learning para el juego pacman.Ingeniero de Sistemas y ...
Martínez Contreras, Juan Pablo
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SSRN Electronic Journal, 2022 70 pages, 4 figures, appended with an ...
Yanwei Jia, Xun Yu Zhou
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A Q-Learning Proposal for Tuning Genetic Algorithms in Flexible Job Shop Scheduling Problems
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Genetic algorithms (GAs) belong to the category of evolutionary algorithms and are frequently utilized for resolving challenging combinatorial problems.
Christian Perez +2 more
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