The Essence of Interaction in Boundedly Complex, Dynamic Task Environments

Abstract

Studying the essence of interaction requires task environments in which changes may arise due to the nature of the environment or the actions of agents in that environment. In dynamic environments, the agent’s choice to do nothing does not stop the task environment from changing. Likewise, making a decision in such environments does not mean that the best decision, based on current information, will remain “best” as the task environment changes. This chapter summarizes work in progress which brings the tools of experimental psychology, machine learning, and advanced statistical analyses to bear on understanding the complexity of interactive performance in complex tasks involving single or multiple interactive agents in dynamic environments.