From Representational Intelligence to Contextual Intelligence in the Simulation of Complex Social Systems

In this paper we explore the uses, advantages and limitations of two different paradigms in the computational simulation of complex social systems. We focus particularly on the simulation of cognitive mechanisms in social situations and illustrate our discussion with two of our current projects. We compare the now classical agent based approach (epitomized by models such as Sugarscape [Epstein & Axtell, 1996]) with an approach in which the computational agents are driven by users. We argue that cognitive mechanisms are still not understood well enough for us to be able to derive convincing rules for guiding interaction and that any intelligence exhibited by such systems are constrained by the rule representation. What we are essentially losing by substituting the human for a rule governed agent is the contextual intelligence that the human can provide in that situation. Any human response to a situation or artefact is based upon a multitude of interacting factors. A human will see, and then interpret the situation knowing the history of the interaction, using their own cultural background, drawing upon their own experience, and with a specific perception of other people and artifacts in that environment, etc. By employing this contextual intelligence, we argue that the behavior of the agents and the overall behavior of the system is closer to what would be expected in reality. Contact: Dr Julie Dugdale GRIC – IRIT UPS-CNRS (UMR 5505), 118 route de Narbonne 31062 Toulouse, France Tel: +33 5 61 55 77 07 Fax : +33 5 61 55 77 08 Email: [email protected]