Results 31 to 40 of about 241,763 (280)
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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Sparse cooperative Q-learning [PDF]
Twenty-first international conference on Machine learning - ICML '04, 2004 Learning in multiagent systems suffers from the fact that both the state and the action space scale exponentially with the number of agents. In this paper we are interested in using Q-learning to learn the coordinated actions of a group of cooperative agents, using a sparse representation of the joint state-action space of the agents.
Kok, J.R., Vlassis, N.
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Q LEARNING REGRESSION NEURAL NETWORK [PDF]
Neural Network World, 2018 In this work, a Nadaraya-Watson kernel based learning system which owns general regression neural network topology is adapted to Q learning method to evaluate a quick and efficient action selection policy for reinforcement learning problems. By means of the proposed method Q value function is generalized and learning speed of Q agent is accelerated ...
Sangiil M., Ave M.
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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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Q Learning Behavior on Autonomous Navigation of Physical Robot [PDF]
, 2011 Behavior based architecture gives robot fast and reliable action. If there are many behaviors in robot, behavior coordination is needed. Subsumption architecture is behavior coordination method that give quick and robust response.
Wicaksono, Handy
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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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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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Energies, 2021 In this paper, two universal reinforcement learning methods are considered to solve the problem of maximum power point tracking for photovoltaics. Both methods exhibit fast achievement of the MPP under varying environmental conditions and are applicable ...
Kostas Bavarinos +2 more
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