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Chapter 13BUILDING EMPIRICALLY PLAUSIBLEMULTI-AGENT SYSTEMSA Case Study of Innovation DiffusionEdmund ChattoeDepartment of Sociology, University of OxfordAbstractMulti-Agent Systems (MAS) have great potential for explaining interactionsamong heterogeneous actors in complex environments: the primary task of socialscience. I shall argue that one factor hindering realisation of this potential is theneglect of systematic data use and appropriate data collection techniques. Thediscussion will centre on a concrete example: the properties of MAS to modelinnovation diffusion.1. IntroductionSocial scientists are increasingly recognising the potential of MAS to castlight on the central conceptual problems besetting their disciplines. Takingexamples from sociology, MAS is able to contribute to our understanding ofemergence [11], relations between micro and macro [4], the evolution of stratification[5] and unintended consequences of social action [9]. However, I shallargue that this potential is largely unrealised for a reason that has been substantiallyneglected: the relation between data collection and MAS design. Ishall begin by discussing the prevailing situation. Then I shall describe a casestudy: the data requirements for MAS of innovation diffusion. I shall thenpresent several data collection techniques and their appropriate contribution tothe proposed MAS. I shall conclude by drawing some more general lessonsabout the relationship between data collection and MAS design.2. Who Needs Data?At the outset, I must make two exceptions to my critique. The first is to acknowledgethe widespread instrumental use of MAS. Many computer scientists