Animal-like adaptive behavior

Abstract

This article reviews basic principles of animal learning and their potential contribution to the adaptation of user interfaces. The principles of classical conditioning, as well as a model that predicts most of the conditioning phenomena, are exposed. This paradigm has been widely studied in fields like Psychology, Biology and Computational Neuroscience, since the properties for stimuli association observed in experiments defined under this principle are important for the understanding of human and animal behavior. We present a direct application of these computational properties to the development of a certain kind of intelligent user interface. The main contribution is a general methodology for intelligent interfaces definition that can adapt themselves in an on-line fashion and without any a priori information of their interaction with the user. This adaptive paradigm outperforms conventional human–interface interaction, yielding more elaborated patterns of behavior where spatial and temporal associations among stimuli play an important 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. Finally, the proposed paradigm is shown to successfully accomplish the adaptation of a customized interface in order to speed up its interaction with the user. The main differences with traditional sequence learning models are also discussed.