50 International Journal of Agent Technologies and Systems, 4(3), 50-72, July-September 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Keywords: Agent Based Modeling, Detail, Expectancy Theory, Information Foraging, Knowledge Spillover, ODD Protocol, Open Source Science, Science of Science 1. INTRODUCTION Knowledge spillovers are studied widely in literature and linked to innovation measures and outputs (Jaffe, 2008; Feldman & Audretsch, 1996). Spillovers are defined as the migration of knowledge beyond the domain borders (Fal- lah & Ibrahim, 2004). In our study, spillovers are not only expressed in terms of knowledge transfer but also mobility of scientists. Hence, spillovers result in formation of new domains as a consequence of knowledge and skill transfer. A research question of interest is to examine the connection between individual rationality and aggregate efficiency. Axtell and Epstein (2006) discuss empirical data, which demon- strate that all individuals should not necessarily be rational to produce efficiency in macro level outcomes of a system. Given that individual rationality is bounded, authors explore how much rationality should exist in a system to generate desirable macro-level patterns. In this An Information Foraging Model of Knowledge Creation and Spillover Dynamics in Open Source Science Özgür Özmen, Auburn University, USA Levent Yilmaz, Auburn University, USA ABSTRACT Motivation and problem-domain preferences of scientists can affect aggregate level emergence and growth of problem domains in science. An agent-based model based on information foraging and expectancy theory is introduced to examine the impact of rationality and openness on the growth and evolution of scientifc domains. To promote reproducibility of the simulation, a standard documentation protocol is used to specify the conceptual model. In the presented virtual socio-technical model, scientists with different preferences search for problem domains to contribute knowledge, while considering their motivational gains. Problem domains become mature and knowledge spills occur over time to facilitate creation of new problem domains. Experiments are conducted to demonstrate emergence and growth of clusters of domains based on local inter- actions and preferences of scientists. Based on fndings, potential avenues of future research are delineated. DOI: 10.4018/jats.2012070104