Publications

In exploring the question of how humans reason in ambiguous situations or in the absence of complete information, we stumbled onto a body of knowledge that addresses issues beyond the original scope of our effort. We have begun to understand the importance that philosophy, in particular the work of C. S. Peirce, plays in developing models of human cognition and of information theory in general. We have a foundation that can serve as a basis for further studies in cognition and decision making. Peircean philosophy provides a foundation for understanding human reasoning and capturing behavioral characteristics of decision makers due to cultural, physiological, and psychological effects. The present paper describes this philosophical approach to understanding the underpinnings of human reasoning. We present the work of C. S. Peirce, and define sets of fundamental reasoning behavior that would be captured in the mathematical constructs of these newer technologies and would be able to interact in an agent type framework. Further, we propose the adoption of a hybrid reasoning model based on his work for future computational representations or emulations of human cognition.

This paper provides an overview John Holland's Echo model, describes an implementation of the model, documents results from preliminary experiments using the model, and proposes further research in using Echo to study complex adaptive systems. Echo simulates the behavior of complex adaptive systems and can provide an experimental testbed for exploring theories of, and developing tools useful for analyzing these systems. Preliminary results indicate that the dynamic behavior of Echo can be used to generate interesting, time-series data that will be useful for evaluating the applicability of and developing tools, techniques, and possibly general theories, for the analysis of specific complex adaptive systems.