Intelligent agent behavior based on organizational image theory

Image theory has been used, in numerous studies, as a basis for understanding and describing the decision‐making activity of managers in both cooperative and competitive environments. The fundamental division of duties prescribed by image theory – namely adoption decisions and progress decision – maps very well to the adaptability requirements of intelligent agents. The issues of adaptive planning and execution monitoring in agents can be well served by applying the empirical lessons learned from the application of image theory across groups of decision makers. This paper explores the concepts of adoption and progress decisions in the context of image theory and provides a basis for creating image‐theoretic agents. This paper sets the foundation for an interdisciplinary bridge between Beach and Mitchell’s Image Theory for human decision making, and the construction of intelligent agents. We begin by presenting image theory and describing its use among human decision makers. We then show how the mechanisms of image theory can be implemented in an agent‐based architecture to implement both execution monitoring and adaptive planning. This is done through the image‐theoretic constructs of progress decisions and adoption decisions. We conclude by presenting logic‐programming implementation of the Imaginal Agent Architecture that supports the adaptive planning and execution monitoring of agents through the use of meta‐level constructs for adoption and progress decisions.