Model-Based Reasoning in Scientific Discovery

The volume is based on the papers that were presented at the Interna tional Conference Model-Based Reasoning in Scientific Discovery (MBR'98), held at the Collegio Ghislieri, University of Pavia, Pavia, Italy, in December 1998. The papers explore how scientific thinking uses models and explanatory reasoning to produce creative changes in theories and concepts. The study of diagnostic, visual, spatial, analogical, and temporal rea soning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of tradi tional notions of reasoning such as classical logic. Traditional accounts of scientific reasoning have restricted the notion of reasoning primarily to de ductive and inductive arguments. Understanding the contribution of model ing practices to discovery and conceptual change in science requires ex panding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. The study of these heuristic ways of reasoning is situated at the crossroads of philoso phy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model based reasoning to be considered in this book. The models are intended as in terpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain.

Klappentext

The book Model-Based Reasoning in Scientific Discovery, aims to explain how specific modeling practices employed by scientists are productive methods of creative changes in science. The study of diagnostic, visual, spatial, analogical, and temporal reasoning has demonstrated that there are many ways of performing intelligent and creative reasoning which cannot be described by classical logic alone. The study of these high-level methods of reasoning is situated at the crossroads of philosophy, artificial intelligence, cognitive psychology, and logic: at the heart of cognitive science. Model based reasoning promotes conceptual change because it is effective in abstracting, generating, and integrating constraints in ways that produce novel results. There are several key ingredients common to the various forms of model-based reasoning to be considered in this presentation. The models are intended as interpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. In the modeling process, various forms of abstraction, such as limiting case, idealization, generalization, and generic modeling are utilized. Evaluation and adaptation take place in the light of structural of structural, causal, and/or functional constraint satisfaction and enhanced understanding of the target problem is obtained through the modeling process. Simulation can be used to produce new states and enable evaluation of behaviors, constraint satisfaction, and other factors. The book also addresses some of the main aspects of the concept of abduction, connecting it to the central epistemological question of hypothesis withdrawal in science and model-based reasoning, where abductive interferences exhibit their most appealing cognitive virtues. The most recent results and achievements in the above areas are illustrated in detail by the various contributors to the work, who are among the most respected researchers in philosophy, artificial intelligence and cognitive science.

Inhalt
Models, Mental Models, and Representations.- Model-Based Reasoning in Conceptual Change5.- Tracing the Development of Models in the Philosophy of Science.- Using Models to Represent Reality.- Models and Diagrams within the Cognitive Field.- Theories, Models, and Representations.- How Scientists Build Models InVivo Science as a Window on the Scientific Mind.- Discovery Processes and Mechanisms.- A Simulation of Model-Based Reasoning about Disparate Phenomena.- Scientific Discovery and Technological Innovation: Ulcers, Dinosaur Extinction, and the Programming Language Java.- A Hierarchy of Models and Electron Microscopy.- Expansion and Justification of Models: the Exemplary Case of Galileo Galilei.- Simplifying Bayesian Inference: the General Case.- Complexity versus Complex Systems: A New Approach to Scientific Discovery.- Creative Inferences and Abduction.- Model-Based Reasoning in Creative Processes.- Model-Based Creative Abduction.- Abduction and Geometrical Analysis. Notes on Charles S. Peirce and Edgar Allan Poe.- The Hierarchy of Models in Simulation.- Fictionalism and the Logic of As If Conditionals.- Scientific Modeling: A Multilevel Feedback Process.- Author Index.