This invention relates to an information processing device and method that enable generation of an unlearned new pattern. Data x.sub.t corresponding to a predetermined time series pattern is inputted to an input layer (11) of a recurrent neural network (1), and a prediction value x*.sub.t+1 is acquired from an output layer 13. A difference between teacher data x.sub.t+1 and the prediction value x*.sub.t+1 is learned by a back propagation method, and a weighting coefficient of an intermediate layer 12 is set at a predetermined value. After the recurrent neural network is caused to learn plural time series patterns, a parameter having a different value from the value in learning is inputted to parametric bias nodes (11-2), and an unlearned time series pattern corresponding to the parameter is generated from the output layer (13). This invention can be applied to a robot.