David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
Philosophy of Science 73 (5):699-709 (2006)
This paper examines the nature of model-based reasoning in the interplay between theory and experiment in the context of biomedical engineering research laboratories, where problem solving involves using physical models. These "model systems" are sites of experimentation where in vitro models are used to screen, control, and simulate specific aspects of in vivo phenomena. As with all models, simulation devices are idealized representations, but they are also systems themselves, possessing engineering constraints. Drawing on research in contemporary cognitive science that construes cognition as occurring in a complex distributed system comprising people and artifacts, I argue that reasoning with model systems is a constraint satisfaction process involving co-construction, manipulation, and revision of mental and physical models.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
Nancy Cartwright (1983). How the Laws of Physics Lie. Oxford University Press.
Lawrence W. Barsalou (1999). Perceptual Symbol Systems. Behavioral and Brain Sciences 22 (4):577-660.
Andy Clark (2003). Natural-Born Cyborgs: Minds, Technologies and the Future of Human Intelligence. Oxford University Press.
Ronald N. Giere (1991). Explaining Science: A Cognitive Approach. Philosophical Review 100 (4):653-656.
Citations of this work BETA
Hyundeuk Cheon (2014). Distributed Cognition in Scientific Contexts. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 45 (1):23-33.
Mohd Hazim Shah bin Abdul Murad (2011). Models, Scientific Realism, the Intelligibility of Nature, and Their Cultural Significance. Studies in History and Philosophy of Science Part A 42 (2):253-261.
Similar books and articles
Lorenzo Magnani, Walter Carnielli & Claudio Pizzi (eds.) (2010). MODEL-BASED REASONING IN SCIENCE AND TECHNOLOGY. Springer.
Nicola Angius & Guglielmo Tamburrini (2011). Scientific Theories of Computational Systems in Model Checking. Minds and Machines 21 (2):323-336.
Ronald N. Giere (2004). The Problem of Agency in Scienti?C Distributed Cognitive Systems. Journal of Cognition and Culture 4 (3-4):759-774.
Ronald N. Giere (2007). Distributed Cognition Without Distributed Knowing. Social Epistemology 21 (3):313 – 320.
Patricia H. Miller (2001). Developmental Issues in Model-Based Reasoning During Childhood. Mind and Society 2 (2):49-58.
Ronald N. Giere (2006). The Role of Agency in Distributed Cognitive Systems. Philosophy of Science 73 (5):710-719.
Rebecca Kukla (1992). Cognitive Models and Representation. British Journal for the Philosophy of Science 43 (2):219-32.
Added to index2009-01-28
Total downloads37 ( #105,336 of 1,790,308 )
Recent downloads (6 months)3 ( #267,458 of 1,790,308 )
How can I increase my downloads?