Can Agent-Based Models Assist Decisions on Large-Scale Practical Problems: A Philosophical Analysis

Gross, C. and Strand, R. (2000) Can Agent-Based Models Assist Decisions on Large-Scale Practical Problems: A Philosophical Analysis. Complexity, 5 (5). pp. 26-33. ISSN 1076-2787 . (Full text available)

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http://dx.doi.org/10.1002/1099-0526(200007/08)5:6<...

Abstract

The use of predictive agent-based models as decision assisting tools in practical problems has been proposed. This article aims at a theoretical clarification of the conditions for such use under what has been called post-normal problems, characterized by high stakes, high and possibly irreducible uncertainties, and high systemic complexity. Our argument suggests that model validation is often impossible under post-normal conditions; however, predictive models can still be useful as learning devices (heristic purposes, formal Gedanken experiments). In this case, micro-structurally complex models are to be preferred to micro-structurally simple ones; this is illustrated by means of two examples.

Item Type: Article
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 27 Aug 2009 13:10
Last Modified: 06 Sep 2011 04:12
Resource URI: http://kar.kent.ac.uk/id/eprint/22067 (The current URI for this page, for reference purposes)
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