Search Results - "Q-learning"

Mobile robot path planning using q-learning with guided Distance by Ee, Soong Low, Pauline, Ong, Cheng, Yee Low

“…In path planning for mobile robot, classical Q-learning algorithm requires high iteration counts and longer time taken to achieve conver-gence. …”
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Q-learning whale optimization algorithm for test suite generation with constraints support by Hassan, Ali Abdullah, Salwani, Abdullah, Kamal Z., Zamli, Rozilawati, Razali

“…This paper introduces a new variant of a metaheuristic algorithm based on the whale optimization algorithm (WOA), the Q-learning algorithm and the Exponential Monte Carlo Acceptance Probability called (QWOA-EMC). …”
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Collision prediction based q-learning for mobile robot navigation in unknown dynamic environments by Findi, Ahmed H. M., Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil, Hassan, Mohd Khair

“…Q-learning (QL) approach is constantly used for mobile robot (MR) navigation in unknown dynamic environment because of its simplicity and well-developed theory. …”
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Solving the optimal path planning of a mobile robot using improved Q-learning by Low, Ee Soong, Ong, Pauline, Cheah, Kah Chun

“…Yet, despite such advantage, Q-learning exhibits slow convergence to the optimal solution. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Adil Soomro, Zubair, Adrianshah, Andi

“…A comparison of both Q-learning and State-ActionReward-State-Action (SARSA) based systems in autonomous drone application was performed for evaluation in this study. …”
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Modified Q-learning with distance metric and virtual target on path planning of mobile robot by Ee, Soong Low, Ong, Pauline, Cheng, Yee Low, Omar, Rosli

“…One of the popular path planners is Q-learning – a type of reinforcement learning that learns with little or no prior knowledge of the environment. …”
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A Deep Q-Learning Framework for Enhanced QoE and Energy Optimization in Fog Computing by Sumona, S.T., Sabbir Hasan, S., Tamzid, A.Y., Roy, P., Razzaque, M.A., Mahmud, Md Redowan

“…Given the NP-hard nature of this framework, we have devised a Deep Q-Learning (DQL) based model for task offloading, termed ELTO-DQL, which aims for near-optimal solutions in polynomial time. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization by Kamal Zuhairi, Zamli, Din, Fakhrud, Alhadawi, Hussam S.

“…This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. …”
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

“…The computation time complexity of the Q-Learning-based test coverage algorithm was also analyzed. …”
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A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem by Kamal Z., Zamli, Fakhrud, Din, Ahmed, Bestoun S., Bures, Miroslav

“…In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Ee Soong Low, Ee Soong Low, Pauline Ong, Pauline Ong, Cheng Yee Low, Cheng Yee Low

“…This study proposes an improved Q-learning (IQL) algorithm to address the challenges of path planning in such environments. …”
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Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model by Kareem Thajeel, Isam, Samsudin, Khairulmizam, Hashim, Shaiful Jahari, Hashim, Fazirulhisyam

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Intelligent handover triggering mechanism in 5G ultra-dense networks via clustering-based reinforcement learning by Liu, Qianyu, Kwong, Chiew Foong, Wei, Sun, Li, Lincan, Zhang, Sibo

Subjects: “…Handover management; Q-learning; Subtractive clustering; Ultra-dense networks…”
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A smart cache content update policy based on deep reinforcement learning by Li, Lincan, Kwong, Chiew Foong, Liu, Qianyu, Wang, Jing

Subjects: “…cache; deep reinforcement learning (DRL); deep Q-learning network (DQN); content update; cache hit ratio; average latency; spatiotemporally varying…”
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

“…YOLOv7 is chosen as the object detection algorithm to detect sun, while Q-learning is chosen as the algorithm for reinforcement learning to control the motors. …”
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Collision prediction- based genetic network programming -reinforcement learning for mobile robot adaptive navigation in unknown dynamic environments by Mohammed, Ahmed Hassan

“…Moreover, it aims to tackle CoD problem of Q-Learning (QL) to be suitable for complex applications. …”
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Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband by Shamshirband, Shahaboddin

“…We investigate the detection capability based on the fuzzy Q-learning (FQL) algorithm and evaluate it using distribute denial of service attacks (DDoS). …”
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Artificial intelligent integrated sun-tracking system with sun and cloud positions prediction by Huang, Dick Shen

“…After successfully tracked the sun’s coordinate, Q-learning will be applied to control the motor in order to follow the sun. …”
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