Abstract

Chaos, once considered antithetical to scientific law and order, is presently the subject of a vigorous and progressive scientific research program. "Chaos" as it is used in current scientific literature is a technical term: it refers to stochastic behavior generated by deterministic systems. This behavior has appeared in models of a wide range of phenomena including atmospheric patterns, population dynamics, celestial motion, heartbeat rhythms, turbulent fluids, chemical reactions and social structures. In general, chaos arises in the nonlinear dynamics of complex systems. Grebogi, Ott and Yorke reflect the sentiment of the scientific community when they state that chaotic nonlinear dynamics has "fundamental implications." This dissertation explores these results in a philosophic context. ;The research is organized as follows: The Context of Science. Scientific results are achieved in and make sense in the practical context of research which includes both experiment and theory. Drawing on the work of Dyke, Galison, Garfinkel and Hacking, a philosophic context is described which more accurately reflects the significance of scientific results than do the contexts of discovery and justification. Models. Chaos theory is constituted by a family of numerical models. In this chapter, Giere's account of modeling is extended to both bio-medical and numerical models. Chaos in Scientific Models. This is a rather lengthy primer of chaos theory that is, although technically accurate, accessible to nonspecialists. It constitutes a road map for the primary literature on chaos. Chaos and Prediction. Chaos theory shows a limit of our science, namely, chaotic systems are deterministic yet unpredictable in the long run. The chapter includes a discussion of scientific determinism following Popper and, it concludes by providing evidence against the laplacian claim that deterministic systems are predictable. Chaos and Complexity. This shows what contribution chaos theory makes toward answering the challenge of organized complexity articulated by Weaver. It discusses attempts to characterize complexity and shows how the results of chaos theory can help. I draw on the work of Abraham, Arecchi, Atlan, Chaitin, Eckmann, Peacocke, Rosen, Ruelle, and others. Chaos theory provides a thoroughly nonvitalistic framework for understanding dynamical complexity in organic, as well as inorganic, systems