Suchergebnisse - "Q Learning Algorithm"

Integrated information system based on Q-learning algorithm and multi-objective particle swarm optimization with molecular fuzzy-based decision-making for corporate environmental investments von Dinçer, Hasan, Yüksel, Serhat, Olaru, Gabriela Oana, Eti, Serkan

“… First, the balanced expert dataset is generated via Q-learning algorithm and multi-objective particle swarm optimization …”
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Walking control of semi-passive robot via a modified Q-learning algorithm von Sun, Zhongkui, Zhou, Yining, Xu, Wei, Wang, Yuexin

“… The analysis and control of stability of passive biped robot has been the subject of an in-depth study because of its unique characteristics …”
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Q-learning algorithm and molecular fuzzy multi-objective particle swarm optimization-based decision-making approach to circular economy-oriented investment alternatives for renewable energy technologies von Dinçer, Hasan, Yüksel, Serhat, Eti, Serkan, Olaru, Gabriela Oana, Deveci, Muhammet, Wu, Qun, Castillo, Oscar

“… The first stage is related to the constructing the balanced expert dataset using Q-learning algorithm …”
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An Experimental Safety Response Mechanism for an Autonomous Moving Robot in a Smart Manufacturing Environment Using Q-Learning Algorithm and Speech Recognition von Kiangala, Kahiomba Sonia, Wang, Zenghui

“… for them. Operators are subject to frequent safety inductions to react in emergencies, but very little is done for robots …”
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Application of Q-learning algorithm based on heterogeneous sensor networks in higher education teaching management von Xie, Qian

“… In this article, the Q-learning algorithm, specifically applied to a heterogeneous cellular network, is employed to investigate the issues pertaining to teaching management in colleges …”
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Stochastic linear quadratic optimal tracking control for discrete-time systems with delays based on Q-learning algorithm von Tan, Xufeng, Li, Yuan, Liu, Yang

“… Based on this, Q-learning algorithm is proposed and its convergence is proved. Finally, a simulation example shows the effectiveness of the proposed algorithm …”
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Research on the Innovative Path of College English Teaching Based on Deep Reinforcement Learning von Zhang, Yumei, Cheng, Hongmei

“… College English is a very flexible and important subject that needs to be constantly innovated …”
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Reinforcement Learning Accelerator using Q-Learning Algorithm with Optimized Bit Precision von Sutisna, Nana, Ilmy, Andi M. R., Setiawan, Handi Nugroho, Syafalni, Infall, Mulyawan, Rahmat, Ahmadi, Nur, Adiono, Trio

“… This paper presents a Reinforcement Learning (RL) accelerator using Q-learning algorithm with optimized bit precision …”
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A Q-Cube Framework of Reinforcement Learning Algorithm for Continuous Double Auction among Microgrids von Wang, Ning, Xu, Weisheng, Shao, Weihui, Xu, Zhiyu

“… In this paper, we investigate the potential of applying a Q-learning algorithm into a continuous double auction mechanism …”
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An Adaptive Q-Learning Algorithm Developed for Agent-Based Computational Modeling of Electricity Market von Rahimiyan, Morteza, Mashhadi, Habib Rajabi

“… ) parameters to the condition of dynamic uncertain environment has always been a significant subject of interest in the context of reinforcement learning …”
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Market Design for a High-Renewables Electricity System

“… The book provides assessments and evaluations of emerging trends in the electricity markets, with a focus on high-renewables electricity systems. Specifically, …”
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Testing Different Reinforcement Learning Configurations for Financial Trading: Introduction and Applications von Bertoluzzo, Francesco, Corazza, Marco

“… The construction of automatic Financial Trading Systems (FTSs) is a subject of research of high interest for both academic environment and financial one due …”
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A novel Q-learning algorithm with function approximation for constrained Markov decision processes von Lakshmanan, K., Bhatnagar, S.

“… We present a novel multi-timescale Q-learning algorithm for average cost control in a Markov decision process subject to multiple inequality constraints …”
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Research on comprehensive assessment of regional renewable energy consumption in the electricity market environment von Cai, Qiuna, Dong, Kai, Wu, Guobing, Lu, En, Chen, Zhongfei, Li, Yupeng, Jing, Zhaoxia

“… Then, based on the Q-learning reinforcement learning algorithm, a multi-agent market clearing model regarding the subject's quotation strategy under imperfect competition was established …”
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Subject sensitive EEG discrimination with fast reconstructable CNN driven by reinforcement learning: A case study of ASD evaluation von Dong, Heyou, Chen, Dan, Zhang, Lei, Ke, Hengjin, Li, Xiaoli

“… This is the case especially in the paradigms that sensitive to the individuality of subjects and the non-stationarity of cognitive dynamics, such as Autism Spectrum Disorder (ASD) evaluation …”
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Q-LEARNING WITH CENSORED DATA von Goldberg, Yair, Kosorok, Michael R

“… We present a novel Q-learning algorithm that is adjusted for censored data and allows a flexible number of stages …”
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An iterative Q-learning based global consensus of discrete-time saturated multi-agent systems von Long, Mingkang, Su, Housheng, Wang, Xiaoling, Jiang, Guo-Ping, Wang, Xiaofan

“… In this paper, motivated by the reinforcement learning method, we propose a model-free Q-learning algorithm to obtain the LGF matrices for the DTMASs achieving global consensus …”
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Lévy noise promotes cooperation in the prisoner’s dilemma game with reinforcement learning von Wang, Lu, Jia, Danyang, Zhang, Long, Zhu, Peican, Perc, Matjaž, Shi, Lei, Wang, Zhen

“… by Lévy distributed noise are reflected in the payoff matrix of each player. At the same time, the self-regarding Q -learning algorithm is considered as the strategy update rule to learn the behavior that achieves the highest payoff …”
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Condition-based maintenance for redundant systems considering spare inventory with stochastic lead time von Wang, Jun, Fu, Yuqiang, Zhou, Jian, Yang, Lechang, Yang, Yating

“… •Stochastic maintenance time and spare ordering lead time are considered.•An improved Q-learning algorithm is proposed with convergence proved …”
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Risk-sensitive reinforcement learning von Shen, Yun, Tobia, Michael J, Sommer, Tobias, Obermayer, Klaus

“… We derive a risk-sensitive Q-learning algorithm, which is necessary for modeling human behavior when transition probabilities …”
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