Optimal control is a very important field of study not only in theory but in applications, and stochastic optimal control is also a significant branch of research in theory and applications. Based on the concept of fuzzy process introduced by Liu, we present a fuzzy optimal control problem. Applying Bellman’s optimal principle, we obtain the principle of optimality for fuzzy optimal control, an...

Model-based reinforcement learning methods are known to be highly efficient with respect to the number of trials required for learning optimal policies. In this article, a novel fuzzy model-based reinforcement learning approach, fuzzy prioritized sweeping (F-PS), is presented. The approach is capable of learning strategies for Markov decision problems with continuous state and action spaces. Th...

− This paper presents a proposed neural fuzzy network tuned by genetic algorithm (GA). By introducing a switch to each rule, the optimal number of rules can be learned. The membership functions of the neural fuzzy network are also tuned by GA. After training, the proposed neural fuzzy network is employed to interpret graffiti number inputs and commands for Electronic Books (eBooks). I. INTRODUC...

In this paper we consider a global optimization approach for solving fuzzy fractional posynomial geometric programming problems. The problem of concern involves positive trapezoidal fuzzy numbers in the objective function. For obtaining an optimal solution, Dinkelbach’s algorithm which achieves the optimal solution of the optimization problem by means of solving a sequence of subproblems ...

This paper deals with a novel method for solving optimal control problems based on genetic programming. This approach produces some trial solutions and seeks the best of them. If the solution cannot be expressed in a closed analytical form then our method produces an approximation with a controlled level of accuracy. Using numerical examples, we will demonstrate how to use the results.

In this paper‎, ‎a computational approach is adopted for solving a multi-objective optimal control problem (MOOCP) formulation of optimal drug scheduling in human immunodeficiency (HIV) virus infected by individuals‎. ‎The MOOCP‎, ‎which uses a mathematical model of HIV infection‎, ‎has some incompatible objectives‎. ‎The objectives are maximizing the survival time of patients‎, ‎the level of D...