Search Results - "Kernel-based Reinforcement Learning"

Kernel-Based Reinforcement Learning by Ormoneit, Dirk, Sen, Śaunak

“…We present a kernel-based approach to reinforcement learning that overcomes the stability problems of temporal-difference learning in continuous state-spaces…”
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Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning by Peng, Xuefeng, Ding, Yi, Wihl, David, Gottesman, Omer, Komorowski, Matthieu, Lehman, Li-Wei H, Ross, Andrew, Faisal, Aldo, Doshi-Velez, Finale

“…Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, tailoring…”
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Adaptive Software-Defined Network Control Using Kernel-Based Reinforcement Learning: An Empirical Study by Nurakhov, Yedil, Kyzyrkanov, Abzal, Otarbay, Zhenis, Lebedev, Danil

“…Software-defined networking (SDN) requires adaptive control strategies to handle dynamic traffic conditions and heterogeneous network environments…”
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Dynamic Selection of p-norm in Linear Adaptive Filtering via online Kernel-based Reinforcement Learning by Vu, Minh, Akiyama, Yuki, Slavakis, Konstantinos

“…-varying probability density function of the outliers. To this end, an online and data-driven framework is designed via kernel-based reinforcement learning (KBRL…”
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Kernel-based reinforcement learning in average-cost problems by Ormoneit, D., Glynn, P.

“…Reinforcement learning (RL) is concerned with the identification of optimal controls in Markov decision processes (MDPs) where no explicit model of the…”
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Online attentive kernel-based temporal difference learning by Chen, Xingguo, Yang, Guang, Yang, Shangdong, Wang, Huihui, Dong, Shaokang, Gao, Yang

“…Kernel-based reinforcement learning has received increasing attention because it requires less prior knowledge linear approximation and neural networks…”
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Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning by Vakili, Sattar

“…Reinforcement Learning (RL) has shown great empirical success in various application domains. The theoretical aspects of the problem have been extensively…”
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Kernel-Based Reinforcement Learning: A Finite-Time Analysis by Omar Darwiche Domingues, Ménard, Pierre, Pirotta, Matteo, Kaufmann, Emilie, Valko, Michal

“…We consider the exploration-exploitation dilemma in finite-horizon reinforcement learning problems whose state-action space is endowed with a metric. We…”
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Dynamic selection of p-norm in linear adaptive filtering via online kernel-based reinforcement learning by Vu, Minh, Akiyama, Yuki, Slavakis, Konstantinos

“… To this end, an online and data-driven framework is designed via kernel-based reinforcement learning (KBRL…”
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Kernel-based reinforcement learning for traffic signal control with adaptive feature selection by Tianshu Chu, Jie Wang, Jian Cao

“…Reinforcement learning in a large-scale system is computationally challenging due to the curse of the dimensionality. One approach is to approximate the…”
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Velocity control in a right-turn across traffic scenario for autonomous vehicles using kernel-based reinforcement learning by Yuxiang Zhang, Bingzhao Gao, Lulu Guo, Hong Chen, Jinghua Zhao

“…Recently, advanced control methods like machine leaning are increasingly applied to autonomous vehicle. This paper focuses on velocity control in a right-turn…”
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Practical Kernel-Based Reinforcement Learning by Barreto, André M S, Precup, Doina, Pineau, Joelle

“…Kernel-based reinforcement learning (KBRL) stands out among reinforcement learning algorithms for its strong theoretical guarantees…”
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Testing Different Reinforcement Learning Configurations for Financial Trading: Introduction and Applications by 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 to…”
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Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning by Peng, Xuefeng, Ding, Yi, Wihl, David, Gottesman, Omer, Komorowski, Matthieu, Lehman, Li-wei H, Ross, Andrew, Faisal, Aldo, Doshi-Velez, Finale

“…Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, tailoring…”
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A kernel-based reinforcement learning approach to stochastic pole balancing control systems by Xin Xu, Peng Chengzhang, Bin Dai, Han-gen He

“… In this paper, a kernel-based reinforcement learning controller is developed for inverted pendulums with unknown dynamics and stochastic disturbances…”
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Achieving Reinforcement Learning Speedup via Quantum Kernel Estimation by Gilvarry, John, Emeakaroha, Vincent C.

“… product suggestions, user notifications and many more. Kernel-based reinforcement learning holds theoretical guarantees of convergence to a unique solution for decision function approximation…”
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State-Following-Kernel-Based Online Reinforcement Learning Guidance Law Against Maneuvering Target by Peng, Chi, Zhang, Hanwen, He, Yongxiang, Ma, Jianjun

“…In this article, a state-following-kernel-based reinforcement learning method with an extended disturbance observer is proposed, whose application to a missile-target interception system is considered…”
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Learning-based Near-optimal Motion Planning for Intelligent Vehicles with Uncertain Dynamics by Lu, Yang, Zhang, Xinglong, Xu, Xin, Yao, Weijia

“… In this paper, a sparse kernel-based reinforcement learning (RL) algorithm with Gaussian Process (GP) Regression (called GP-SKRL…”
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Clustering Based Kernel Reinforcement Learning for Neural Adaptation in Brain-Machine Interfaces by Xiang Zhang, Principe, Jose C., Yiwen Wang

“…Reinforcement learning (RL) interprets subject's movement intention in Brain Machine Interfaces (BMIs) through trial-and-error with the advantage that it does…”
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The Network Optimization Algorithm of PLC Module Automatic Detection Pipeline by Huang, Mei, Geng, Bo, Chen, Zuowei, Yin, Shihong, Qiu, Xing

“… detection units is established. The kernel-based reinforcement learning algorithm(KBRL) is used to realize the optimal allocation of slicing resources…”
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