Model-Based Reasoning in Scientific Discovery

This text aims to explain how specific modelling 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 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 modelling process, various forms of abstraction, such as limiting case, idealization, generalization, and generic modelling 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 modelling process. Simulation can be used to produce new states and enable evaluation of behaviours, 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 cognitive virtues. The recent results and achievements in the above areas are illustrated in detail by the various contributors to the work, who are researchers in philosophy, artificial intelligence and cognitive science.

Table of Contents:
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.