Simulation as Formal and Generative Social Science: The Very Idea

From the very beginning of the multiagent-systems paradigm, the sources of analogies between agent-based technologies and models of actual social systems fomented interdisciplinary efforts between computer and social scientists. Nowadays this trend reflects an intense interface of research across the computer and social sciences, under the umbrella of a consolidated scientific field, which is called agentbased social simulation. Several reasons prompt a philosophical analysis of this scientific domain, relevant to both computer and social scientists that use multiagent systems. Conventional methodologies of computer science and artificial intelligence model the mechanism of executing a program in a computer like a process of formal inference. However, in [1, 2] the formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Particular emphasis is given to agent-based simulation methods. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain agentbased models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Previous works identified three kinds of knowledge that account for a comprehensive description of the discipline: formal, empirical and intentional knowledge [3, 4]. This extended abstract summarizes claims we have further presented in [1] and published in [2]: The use of formal conceptions of computation to describe simulation is refuted, the roles of programming languages according to intentional accounts of computation are identified, and the new role of iconographic programming languages and aesthetic machines in simulation platforms are characterized.