Levins and the lure of artificial worlds.

What is it about simulation models that has led some practitioners to treat them as potential sources of empirical data on the real-world systems being simulated; that is, to treat simulations as ‘artificial worlds’ within which to perform computational ‘experiments’? Here we use the work of Richard Levins as a starting point in identifying the appeal of this model building strategy, and proceed to account for why this appeal is strongest for computational modellers. This analysis suggests a perspective on simulation modelling that makes room for ‘artificial worlds’ as legitimate science without having to accept that they should be treated as sources of empirical data

[1]  Seth Bullock,et al.  Simulation models as opaque thought experiments , 2000 .

[2]  R. Levins The strategy of model building in population biology , 1966 .

[3]  Elliott Sober,et al.  A Critical Assessment of Levins's The Strategy of Model Building in Population Biology (1966) , 1993, The Quarterly Review of Biology.

[4]  Seth Bullock,et al.  Empiricism in artificial life , 2004 .

[5]  N Oreskes,et al.  Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences , 1994, Science.

[6]  D. Marr,et al.  Artificial Intelligence - A Personal View , 1976, Artif. Intell..

[7]  The Nature of Life: Classical and Contemporary Perspectives from Philosophy and Science: Learning from functionalism: prospects for strong artificial life , 2010 .

[8]  Christopher Peacocke,et al.  Explanation in Computational Psychology: Language, Perception and Level 1.5 , 1986 .

[9]  L. S. Vygotskiĭ,et al.  Mind in society : the development of higher psychological processes , 1978 .

[10]  M. Bedau Weak Emergence * , 1997 .

[11]  Phil Husbands,et al.  The View From Elsewhere: Perspectives on ALife Modeling , 2002, Artificial Life.

[12]  J. Moor,et al.  The digital phoenix : how computers are changing philosophy , 1998 .

[13]  Seth Bullock,et al.  Charles Babbage and the emergence of automated reason , 2008 .

[14]  S. Peck Simulation as experiment: a philosophical reassessment for biological modeling. , 2004, Trends in ecology & evolution.

[15]  J M Smith,et al.  Evolution and the theory of games , 1976 .

[16]  Andy Clark,et al.  Connectionism, Competence, and Explanation , 1990, The British Journal for the Philosophy of Science.

[17]  Guy Theraulaz,et al.  Swarm made architectures , 1992 .

[18]  Richard A. Watson Compositional Evolution - The Impact of Sex, Symbiosis, and Modularity on the Gradualist Framework of Evolution , 2006, The Vienna series in theoretical biology.

[19]  J. Fodor,et al.  Learning from functionalism : prospects for strong artificial life , 2022 .

[20]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[21]  V. Tucker,et al.  GLIDING BIRDS: REDUCTION OF INDUCED DRAG BY WING TIP SLOTS BETWEEN THE PRIMARY FEATHERS , 1993 .

[22]  J. Casti Would-Be Worlds: How Simulation Is Changing the Frontiers of Science , 1996 .

[23]  L. Premo,et al.  Agent-based models as behavioral laboratories for evolutionary anthropological research , 2006 .

[24]  Thomas S. Ray,et al.  An Evolutionary Approach to Synthetic Biology: Zen and the Art of Creating Life , 1993, Artificial Life.

[25]  Richard E. Lenski,et al.  The future of evolutionary biology , 2004 .

[26]  John S. McCaskill,et al.  Open Problems in Artificial Life , 2000, Artificial Life.

[27]  Jay Odenbaugh,et al.  Complex Systems, Trade‐Offs, and Theoretical Population Biology: Richard Levin's “Strategy of Model Building in Population Biology” Revisited , 2003, Philosophy of Science.

[28]  J. M. Smith The theory of games and the evolution of animal conflicts. , 1974, Journal of theoretical biology.

[29]  Michael Weisberg,et al.  The structure of tradeoffs in model building , 2009, Synthese.

[30]  J. Hailman Wonderful Life: The Burgess Shale and the Nature of History, Stephen Jay Gould. W. W. Norton, New York (1989), 347, Price $19.95 (U.S.A.), $27.95 (Canada) , 1991 .

[31]  Róbert Ványi,et al.  Compositional evolution: the impact of sex, symbiosis and modularity on the gradualist framework of evolution , 2008, Genetic Programming and Evolvable Machines.

[32]  J. M. Smith,et al.  The Logic of Animal Conflict , 1973, Nature.

[33]  Jay Odenbaugh,et al.  The strategy of “The strategy of model building in population biology” , 2007 .

[34]  W. Hamilton Geometry for the selfish herd. , 1971, Journal of theoretical biology.

[35]  Alastair Channon,et al.  Artificial Life , 2010, Encyclopedia of Machine Learning.