. . "587838" . "26210" . "Bratislav, SK" . "RIV/00216305:26210/04:PU45570" . "Asynchronous electric motor control task can be successfully solved using reinforcement learning based method called Q-learning. The main problem to solve is the convergence speed. Two-phase Q-learning can be used to speed up the learning process. Efficient prelearning phase uses mathematical model and next phase using for tutorage real system. This method can increase learning speed significantly. When the table is used as Q-function approximation, the learning speed and precision of found controllers depend highly on the Q-function table grid properties. The paper is focused on finding the optimal division of grid."@cs . . "Bratislava" . . . "Marada, Tom\u00E1\u0161" . "Stanoven\u00ED optim\u00E1ln\u00EDho rastru Q-funkce pro \u0159\u00EDzen\u00ED asynchronn\u00EDho elektromotoru"@cs . "[621BE0D5D70E]" . . "Determination of Q-function Optimum Grid for Control Task of Asynchronous Electric Motor"@en . "Asynchronous electric motor control task can be successfully solved using reinforcement learning based method called Q-learning. The main problem to solve is the convergence speed. Two-phase Q-learning can be used to speed up the learning process. Efficient prelearning phase uses mathematical model and next phase using for tutorage real system. This method can increase learning speed significantly. When the table is used as Q-function approximation, the learning speed and precision of found controllers depend highly on the Q-function table grid properties. The paper is focused on finding the optimal division of grid."@en . . "Singule, Vladislav" . "Determination of Q-function Optimum Grid for Control Task of Asynchronous Electric Motor"@en . "Stanoven\u00ED optim\u00E1ln\u00EDho rastru Q-funkce pro \u0159\u00EDzen\u00ED asynchronn\u00EDho elektromotoru" . . . "Asynchronous electric motor control task can be successfully solved using reinforcement learning based method called Q-learning. The main problem to solve is the convergence speed. Two-phase Q-learning can be used to speed up the learning process. Efficient prelearning phase uses mathematical model and next phase using for tutorage real system. This method can increase learning speed significantly. When the table is used as Q-function approximation, the learning speed and precision of found controllers depend highly on the Q-function table grid properties. The paper is focused on finding the optimal division of grid." . "V" . "Asynchronous electromotor, Q-learning, Control, PID"@en . . . . . . "Stanoven\u00ED optim\u00E1ln\u00EDho rastru Q-funkce pro \u0159\u00EDzen\u00ED asynchronn\u00EDho elektromotoru"@cs . "5"^^ . "B\u0159ezina, Tom\u00E1\u0161" . "3"^^ . "Stanoven\u00ED optim\u00E1ln\u00EDho rastru Q-funkce pro \u0159\u00EDzen\u00ED asynchronn\u00EDho elektromotoru" . . "Proceedings of the 7th International Symposium %22Topical Questions of Teaching Mechatronics%22" . "3"^^ . "2004-05-24+02:00"^^ . . "80-227-2064-X" . "Slovensk\u00E1 technick\u00E1 univerzita v Bratislave. Strojn\u00EDcka fakulta CA Mechatronika" . . "RIV/00216305:26210/04:PU45570!RIV11-MSM-26210___" . .