Search Results - (( developing agent state algorithm ) OR ( java implication based algorithm ))
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Secured Autonomous Agent-Based Intrusion Detection System (SAAIDS)
Published 2024thesis::master thesis -
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…Moreover, agent-based behavioral models of the nanomotors are developed using state machine diagrams of UML to illustrate the internal autonomous and intelligent decision-making processes of the nanomotors. …”
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3
Agents for Fuzzy Indices of Reliability Power System with Uncertainty Using Monte Carlo Algorithm
Published 2014“…Two agents are developed based on fuzzy parameters of Monte Carlo i.e. current with its means and variances; the other agent is the probability of outage capacity for each state. …”
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The comparison study among optimization techniques in optimizing a distribution system state estimation
Published 2017“…Therefore each measurement model reduces to an underdetermined nonlinear system and in radial distribution systems, the state elements associated with an agent may overlap with neighboring agents. …”
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Estimation-based Metaheuristics: A New Branch of Computational Intelligence
Published 2016“…Besides biology, physics and chemistry, state estimation algorithm also has become a source of inspiration for developing metaheuristic algorithms. …”
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The design for antrophomorphic sociable agent interaction through emotion detection
Published 2003“…This research works addresses on faces features through simulation of anthropomorphic agent.A salience feature of this definition of emotion is described in terms of goals and roles.Therefore, it provides a basic framework of goal-driven processing, which is to investigate computational models of emotion.The main goal of this research is to provide a natural interaction scheme where the affective interaction emotive state of the user can be identified.One aspect of developing such a capability is the ability of the system to recognize emotional state using intelligent supervised learning algorithms, personality of the user and respond appropriately.An anthropomorphic agent will serve to express the reaction through affective feedback given. …”
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CSGO: a game-inspired metaheuristic algorithm for global optimization
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
Published 2015“…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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14
Agent-Based Model of Virtual Community Cohesion (S/O: 13443)
Published 2021“…The formal specifications (differential equations) equations form the basis of algorithm development, which preceded the development of a virtual community cohesion prediction simulator. …”
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Monograph -
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…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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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…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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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…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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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…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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Deep reinforcement learning based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehicles
Published 2022“…Three state-of-the-art contemporary actor-critic algorithms are used to create an extensive simulation in Unity3D. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…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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