Computer Simulations in Science and Technology Studies, Softcover reprint of the original 1st ed. 1998

What is it about the structure and organisation of science and technology that has led to the spectacularly successful growth of knowledge during this century? This book explores this important and much debated question in an innovative way, by using computer simulations. The computer simulation of societies and social processes is a methodology which is rapidly becoming recognised for its potential in the social sciences. This book applies the tools of simulation systematically to a specific domain: science and technology studies. The book shows how computer simulation can be applied both to questions in the history and philosophy of science and to issues of concern to sociologists of science and technology. Chapters in the book demonstrate the use of simulation for clarifying the notion of creativity and for understanding the logical processes employed by eminent scientists to make their discoveries. The book begins with three introductory chapters. The first introduces simulation for the social sciences, surveying current work and explaining the advantages and pitfalls of this new methodology. The second and third chapters review recent work on theoretical aspects of social simulation, introducing fundamental concepts such as self­ organisation and complexity and relating these to the simulation of scientific discovery.

Introducing simulation in social studies of science and technology: N. Gilbert: Simulation: An introduction to the idea.- J. Klüver: Modelling science as an adaptive and self-organising social system: Concepts, theories and modelling tools.- P. Ahrweiler, S. Wörmann: Computer simulations in science and technology studies.- Simulating the logic of discovery: M. May: Causation and discovery.- G. Graßhoff: The discovery of the urea cycle: Computer models of scientific discovery.- R. Vos, F. Rikken: Connecting disconnected structures: The modelling of scientific discovery in medical literature databases.- Evolutionary models of science and technology: K. Troitzsch: The evolution of technologies.- K. Frenken, O. Verbart: Simulating paradgm shifts using a lock-in model.- P. Ahrweiler, R. Wolkenhammer: SiSiFOS - simulating studies on the internal formation and the organization of science.- G. Küppers: The self-organization of social systems: A simulation of the social construction of knowledge.- C. Stoica: Modelling Krohn and Küppers` theory of science as a self-organizing system.- Simulating conditions and dependencies of scientific work: A. Miller: Modelling creativity.- P. Windrum, C. Birchenhall: Developing simulation models with policy relevance: The implications of recent UK reforms for emergent scientific disciplines.