How Modeling Can Go Wrong: Some Cautions and Caveats on the Use of Models

Philosophy and Technology 26 (1):75-80 (2013)
  Copy   BIBTEX

Abstract

Modeling and simulation clearly have an upside. My discussion here will deal with the inevitable downside of modeling — the sort of things that can go wrong. It will set out a taxonomy for the pathology of models — a catalogue of the various ways in which model contrivance can go awry. In the course of that discussion, I also call on some of my past experience with models and their vulnerabilities

Similar books and articles

Agent-based Models as Fictive Instantiations of Ecological Processes.Steven L. Peck - 2012 - Philosophy, Theory, and Practice in Biology 4 (20130604).
The hermeneutics of ecological simulation.Steven L. Peck - 2008 - Biology and Philosophy 23 (3):383-402.
Mathematical Modeling in Biology: Philosophy and Pragmatics.Rasmus Grønfeldt Winther - 2012 - Frontiers in Plant Evolution and Development 2012:1-3.
Ontological aspects of information modeling.Robert L. Ashenhurst - 1996 - Minds and Machines 6 (3):287-394.
Perspectives on Modeling in Cognitive Science.Richard M. Shiffrin - 2010 - Topics in Cognitive Science 2 (4):736-750.
Modeling and experimenting.Isabelle Peschard - 2009 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. Routledge.

Analytics

Added to PP
2012-10-02

Downloads
202 (#95,788)

6 months
52 (#79,641)

Historical graph of downloads
How can I increase my downloads?

Author Profiles

Nicholas Rescher
University of Pittsburgh
Patrick Grim
University of Michigan, Ann Arbor

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references