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This paper proposes a multi-objective reinforcement learning algorithm (MORLA) and uses simultaneous perturbation stochastic approximation (SPSA) to improve the convergence of it. Usually, reinforcement learning (RL) is used to design neurocontroller for control system with single objective. When facing multi-objective system, it is necessary to design the neurocontroller according to the personal...
An efficient and powerful design method suitable for calculating optimal proportional-integral-derivative (PID) controllers for AVR systems is proposed. The method is an improved version of the Discrete Action Reinforcement Learning Automata (DARLA) while discrete probability functions (DPF) of the design variables are not considered independent. The results of the proposed method called Extended...
Generally, reinforcement learning (RL) is used to design neurocontroller for control system with single objective. When facing multi-objective system, it is necessary to design the neurocontroller according to the personal preference. This paper proposed a multi-objective reinforcement learning algorithm (MORLA) to design neurocontroller with the personal preference. It transformed the multi-objective...
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