1. A method for controlling a game character, the method comprising the steps of: analyzing a game situation in which a character appears on a computer; and controlling a behavior of the character depending on a result of the analyzing, wherein the steps of analyzing and controlling are performed using a multilayer perceptron, wherein in the multilayer perceptron, an output value according to an input value is previously learned by a supervised learning method, and then the behavior of the character is controlled, wherein in the supervised learning method, a weight of an output layer is determined to minimize an mean squared error (MSE), wherein the weight of the output layer is calculated using the following equation: 
 w ij(new) l =w ij(old) l +ηδ j l h i l−1 where w η l denotes a weight of the output layer, η denotes a learning rate, and δ i l denotes a differential value of an error of the output layer with respect to each neuron value of a hidden layer.