David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
In science, models are used in many different ways: to test empirical hypotheses, to help in theory formation, to visualize data, and so on. Scientists construct and study the behavior of models, and compare this to observed behavior of a target system. We propose that for this to be possible models must carry information about their targets. When models are viewed as information carrying entities, this property can be used as a foundation for a representational theory of models. This account presents a way of avoiding the need to refer to modelers’ intentions (or their mental states) as constitutive of the semantics of scientific representations. Moreover, an information theory based account of scientific representations can provide a naturalistic account of models which can deal the problems of asymmetry, relevance and circularity that afflict currently popular proposals based on user intentions. From the information semantic perspective, models as scientific representations can be considered a special case of a larger problem of naturalistic representation. In this paper we will look at what we think is the most promising avenue of developing this information theoretic account of representational models. Traditionally, there has been a strong tendency towards a clear-cut division of labor between philosophers of science and philosophers of mind. We believe that there are some important philosophical insights about representation that are relevant for both camps.
|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
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Uskali Mäki (2009). MISSing the World. Models as Isolations and Credible Surrogate Systems. Erkenntnis 70 (1):29 - 43.
Gabriele Contessa (2007). Representing Reality: The Ontology of Scientific Models and Their Representational Function. Dissertation, University of London
Peter Gardenfors (2004). Conceptual Spaces as a Framework for Knowledge Representation. Mind and Matter 2 (2):9-27.
Tarja Knuuttila (2005). Models, Representation, and Mediation. Philosophy of Science 72 (5):1260-1271.
Brian Riordan & Michael N. Jones (2011). Redundancy in Perceptual and Linguistic Experience: Comparing Feature-Based and Distributional Models of Semantic Representation. Topics in Cognitive Science 3 (2):303-345.
Adam Toon (2010). Models as Make-Believe. In Roman Frigg & Matthew Hunter (eds.), Beyond Mimesis and Convention: Representation in Art and Science. Boston Studies in Philosophy of Science
Added to index2009-10-15
Total downloads28 ( #136,634 of 1,792,140 )
Recent downloads (6 months)5 ( #170,928 of 1,792,140 )
How can I increase my downloads?