Animal-like adaptive behavior

This article reviews basic principles of animal learning and their potentia l contribution to the adaptation of user interfaces. The principles of clas sical conditioning, as well as a model that predicts most of the conditioni ng phenomena, are exposed. This paradigm has been widely studied in fields like Psychology, Biology and Computational Neuroscience, since the properti es for stimuli association observed in experiments defined under this princ iple are important for the understanding of human and animal behavior. We p resent a direct application of these computational properties to the develo pment of a certain kind of intelligent user interface. The main contributio n is a general methodology for intelligent interfaces definition that can a dapt themselves in an on-line fashion and without any a priori information of their interaction with the user. This adaptive paradigm outperforms conv entional human-interface interaction, yielding more elaborated patterns of behavior where spatial and temporal associations among stimuli play an impo rtant role. The achieved upgrading is concerned with a significant effort: understanding user interfaces as living organisms, and identifying the set of stimuli and responses that determine the interaction with the user. Fina lly, the proposed paradigm is shown to successfully accomplish the adaptati on of a customized interface in order to speed up its interaction with the user. The main differences with traditional sequence learning models are al so discussed. (C) 2001 Elsevier Science Ltd. All rights reserved.