Search Results - (( developing effective reward algorithm ) OR ( java implication based algorithm ))

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  1. 1

    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning by Ahmed Abo Mosali, Najm Addin Mohammed

    Published 2022
    “…Fifth, a novel agent selection algorithm was developed to enable the selection of the best agent and avoid under-fitting and over-fitting. …”
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  2. 2

    Twin delayed deep deterministic policy gradient-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage training by Abo Mosali, Najmaddin, Shamsudin, Syariful Syafiq, Alfandi, Omar, Omar, Rosli, AL-Fadhali, Najib

    Published 2022
    “…With respect to the traditional proportional differential controller, the maximum error reduction rate is 86%. The developed achievement rewarding and the multistage training opens the door to various applications of RL in target tracking.…”
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  3. 3
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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

    Published 2023
    “…According to this simulation process is shows that Q-Learning is a better performance and effective to train the system to achieve desire compared with SARSA algorithm for drone controller.…”
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  5. 5

    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, Zubair Adil Soomro, Zubair Adil Soomro, Andi Adrianshah, Andi Adrianshah

    Published 2023
    “…According to this simulation process is shows that Q-Learning is a better performance and effective to train the system to achieve desire compared with SARSA algorithm for drone controller.…”
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  6. 6

    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, Soomro, Zubair Adil, Adrianshah, Andi

    Published 2023
    “…According to this simulation process is shows that Q-Learning is a better performance and effective to train the system to achieve desire compared with SARSA algorithm for drone controller.…”
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  7. 7

    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

    Published 2023
    “…According to this simulation process is shows that Q-Learning is a better performance and effective to train the system to achieve desire compared with SARSA algorithm for drone controller.…”
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  8. 8
  9. 9

    Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi by Hayder Faeq Rasool , Alhashimi

    Published 2025
    “…Finally, a State-Action-Reward-State-Action (SARSA) algorithm, which is a reinforcement learning approach, is proposed to solve the power allocation optimization problem. …”
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  10. 10

    Efficient node cooperation stimulation mechanism in wireless multihop networks by Samian, Normalia

    Published 2017
    “…Ultimately, a hybrid cooperation stimulation scheme named Recharge-As-Reward (RAR) and Credit-As-Reward (CAR) which functions as an explicit reward (i.e. in the form of token/flag) for cooperative nodes has been proposed in this study. …”
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  12. 12

    Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

    Published 2023
    “…This algorithm is capable of surmounting the aforementioned drawbacks especially premature convergence, through its reward-based dynamic leader assignment and self-learning strategies. …”
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  13. 13

    Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

    Published 2021
    “…The results demonstrate that the adaptation of Q-Learning with UCB exploration can significantly improve the effectiveness of the generated test cases. The computation time complexity of the Q-Learning-based test coverage algorithm was also analyzed. …”
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