ABSTRACT
This chapter shows how complexity theory represents information processing in an unpredictable environment. It examines the interplay between nonlinear dynamical systems and associated evolutionary processes to adjust environmental demands. Experimental psychologists study cognitive phenomena by searching for causal relationships between carefully controlled experimental variables and subsequent values of appropriate dependent variables. The chapter explores the intriguing idea that a complex system, composed of many interacting components, evolves toward optimal information processing at the edge-of-chaos. Applications of complexity theory in psychology included discussions of information processing limitations in cognitive development and the generation of empirically valid decision models based on the Ornstein-Uhlenbeck (OU) stochastic process. The chapter concludes with some speculative remarks on a new research strategy required to examine the evolution of complexity in behavioral systems. Some reassurance is gained when it is realized that complex system behavior might be explained by a relatively small number of basic principles based on evolutionary processes operating in nonlinear dynamic environments.
