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Development of a Modified Random Signal-based Learning using Simulated Annealing

  • Han, Chang-Wook (Department of Electrical Engineering, Dong-Eui University) ;
  • Lee, Yeunghak (Avionics Electronic Engineering, Kyungwoon University)
  • Received : 2015.02.03
  • Accepted : 2015.04.04
  • Published : 2015.03.31
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Abstract

This paper describes the application of a simulated annealing to a random signal-based learning. The simulated annealing is used to generate the reinforcement signal which is used in the random signal-based learning. Random signal-based learning is similar to the reinforcement learning of neural network. It is poor at hill-climbing, whereas simulated annealing has an ability of probabilistic hill-climbing. Therefore, hybridizing a random signal-based learning with the simulated annealing can produce better performance than before. The validity of the proposed algorithm is confirmed by applying it to two different examples. One is finding the minimum of the nonlinear function. And the other is the optimization of fuzzy control rules using inverted pendulum.

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