Data Farming Coevolutionary Dynamics in RePast

13 years 8 months ago
Data Farming Coevolutionary Dynamics in RePast
This paper describes the application of data farming techniques (Brandstein and Horne 1998) to explore various aspects of coevolutionary dynamics (McKelvey 2002) in organization science. Data farming is an iterative process using high-performance computing to execute and vary agent-based models, collect and explore statistical results, and integrate these results for the purposes of growing more data by virtue of generative analysis. The tool of choice for creating these agent-based models is the University of Chicago's Social Science Research Computing's (2004) REcursive Porous Agent Simulation Toolkit (RePast). The paper concludes with a brief description of Tivnan's (2004) Coevolutionary model of Boundary-spanning Agents and Strategic Networks (C-BASN), an extension of Hazy and Tivnan's (2004) Model of Organization, Structural Emergence, and Sustainability (MOSES). 1 DATA FARMING The following discussion provides a general overview of data farming. For in-depth ...
Brian F. Tivnan
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where WSC
Authors Brian F. Tivnan
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