Search Results - (( intelligent agent learning algorithm ) OR ( intelligence based learning algorithm ))

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  1. 1
    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun

    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

    Published 2000
    “…In order to develop an intelligent agent, various programming techniques are used in achieving the property of self learning, information retrieval and searching algorithm. …”
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  2. 2
    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband

    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband by Shamshirband, Shahaboddin

    Published 2014
    “…Later, we investigate the game based-FQL algorithm by combining the game theoretic approach and the fuzzy Q-learning algorithm. …”
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  3. 3
    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing

    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

    Published 2022
    “…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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    Final Year Project / Dissertation / Thesis
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  4. 4
    A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection

    A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection by Basheer G.S., Ahmad M.S., Tang A.Y.C.

    Published 2023
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  5. 5
    Multi-Agent Reinforcement Learning For Swarm Robots Formation

    Multi-Agent Reinforcement Learning For Swarm Robots Formation by Bujang, Christina

    Published 2021
    “…The reinforcement learning algorithm offers one of the most general frameworks in learning subjects to address some of the control issues in a multi-agent system. …”
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    Monograph
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  6. 6
    Q-REINFORCEMENT LEARNING BASED MULTI-AGENT BELLMANFORD ROUTING ALGORITHM FOR SMART MICROGRID COMMUNICATION NETWORK

    Q-REINFORCEMENT LEARNING BASED MULTI-AGENT BELLMANFORD ROUTING ALGORITHM FOR SMART MICROGRID COMMUNICATION NETWORK by SINGH, NIHARIKA

    Published 2021
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  7. 7
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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  8. 8
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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  9. 9
    Automated bilateral negotiation with incomplete information in the e-marketplace.

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
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  10. 10
    Proposal for ontology based approach to fuzzy student model design

    Proposal for ontology based approach to fuzzy student model design by Muhammad Sani, Salisu, Mohd Aris, Teh Noranis

    Published 2014
    “…Intelligent tutoring system (ITS) is a software system designed using artificial intelligent techniques (comprising of Fuzzy Logic, Neural-Networks, Bayesian networks, Ontology, Genetic Algorithms and Software Agents) to provide an adaptive and personalized tutoring suitable to each individual student based on his/her profile or characteristics. …”
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  11. 11
    Enhancing simulated kalman filter algorithm using current optimum opposition-based learning

    Enhancing simulated kalman filter algorithm using current optimum opposition-based learning by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Falfazli, Mat Jusof, Nor Hidayati, Abdul Aziz, Nor Azlina, Ab. Aziz

    Published 2019
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  12. 12
    Object-Oriented Programming semantics representation utilizing agents

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…The running system shows an OOP semantic knowledge representation by intelligent agents.…”
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  13. 13
    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming

    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming by Darzi S., Sieh Kiong T., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

    Published 2023
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  14. 14
    A Principled Design of Intelligent Agent for the SLA negotiation process in cloud computing

    A Principled Design of Intelligent Agent for the SLA negotiation process in cloud computing by Kumar, R., Hassan, M.F., Adnan, M.H.M.

    Published 2022
    “…In the dynamic market of cloud and heterogeneous environments, the existing system needs an intelligent agent-based negotiation system (IANS) to handle responsibilities. …”
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  15. 15
    A Principled Design of Intelligent Agent for the SLA negotiation process in cloud computing

    A Principled Design of Intelligent Agent for the SLA negotiation process in cloud computing by Kumar, R., Hassan, M.F., Adnan, M.H.M.

    Published 2022
    “…In the dynamic market of cloud and heterogeneous environments, the existing system needs an intelligent agent-based negotiation system (IANS) to handle responsibilities. …”
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  16. 16
    Ontology based approach to Fuzzy student model design

    Ontology based approach to Fuzzy student model design by Muhammad Sani, Salisu, Mohd Aris, Teh Noranis

    Published 2014
    “…An important component of these elearning systems in use today is called the intelligent tutoring system (ITS). ITS is a software system designed using artificial intelligent techniques (comprising of Fuzzy Logic, Neural-Networks, Bayesian networks, Ontology, Genetic Algorithms and Software Agents) to provide a personalized tutoring adaptable to each student based on his/her profile or characteristics. …”
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  17. 17
    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Firstly is by enhancing the learning algorithm of a neural-fuzzy network; and secondly by devising an ensemble model to combine the predictions from multiple neural-fuzzy networks using an agent-based framework. …”
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  18. 18
    Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function

    Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

    Published 2019
    “…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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  19. 19
    Neuro Symbolic Integration and Agent Based Modelling

    Neuro Symbolic Integration and Agent Based Modelling by Sathasivam , Saratha, Velavan, Muraly

    Published 2018
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  20. 20
    A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging

    A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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