Title :
Evolutionary trained radial basis function networks for robot control
Author :
Vidnerová, Petra ; Slusny, S. ; Neruda, Roman
Author_Institution :
Inst. of Comput. Sci., Acad. of Sci. of the Czech Republic, Prague
Abstract :
An emergence of intelligent behaviour within a simple robotic agent is studied in this paper. The radial basis function neural network is used as the control mechanism of the robot. Evolutionary algorithm is used to train the agent to perform several tasks. A comparison to multilayer perceptron neural networks and reinforcement learning is made and the results are discussed.
Keywords :
evolutionary computation; learning (artificial intelligence); neurocontrollers; radial basis function networks; robots; evolutionary trained radial basis function networks; multilayer perceptron neural networks; reinforcement learning; robot control; Erbium; Evolutionary computation; Intelligent robots; Mobile robots; Multilayer perceptrons; Neural networks; Radial basis function networks; Robot control; Robot sensing systems; Robotics and automation; RBF networks; evolutionary robotics; genetic algorithms;
Conference_Titel :
Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on
Conference_Location :
Hanoi
Print_ISBN :
978-1-4244-2286-9
Electronic_ISBN :
978-1-4244-2287-6
DOI :
10.1109/ICARCV.2008.4795625
