1A1-X03 Pattern Recognition Based on Associative Memory and Behavior Selection by Utilizing Artificial Neural Network(Evolution and Learning for Robotics)
Sho Nakamura · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2014
This paper describes a novel neural network model for pattern recognition and behavior selection. In the case of constructing a system which can adapt to changing environment and achieve some task, it is necessary for the system to be able to predict current situation and select proper behavior by utilizing memory data and limited observed data. This function is realized by connecting three neural networks in series. Each neural network has a role of prediction, recognition and behavior selection, respectively. In this report, the neural network model is explained, and a simulation result is shown for confirming the idea.