Page 126 - Socially Intelligent Agents Creating Relationships with Computers and Robots

Chapter 13

BUILDING EMPIRICALLY PLAUSIBLE
MULTI-AGENT SYSTEMS

A Case Study of Innovation Diffusion

Edmund Chattoe
Department of Sociology, University of Oxford

Abstract Multi-Agent Systems (MAS) have great potential for explaining interactions
among heterogeneous actors in complex environments: the primary task of social
science. I shall argue that one factor hindering realisation of this potential is the
neglect of systematic data use and appropriate data collection techniques. The
discussion will centre on a concrete example: the properties of MAS to model
innovation diffusion.

1. Introduction

Social scientists are increasingly recognising the potential of MAS to cast
light on the central conceptual problems besetting their disciplines. Taking
examples from sociology, MAS is able to contribute to our understanding of
emergence [11], relations between micro and macro [4], the evolution of strati-
fication [5] and unintended consequences of social action [9]. However, I shall
argue that this potential is largely unrealised for a reason that has been sub-
stantially neglected: the relation between data collection and MAS design. I
shall begin by discussing the prevailing situation. Then I shall describe a case
study: the data requirements for MAS of innovation diffusion. I shall then
present several data collection techniques and their appropriate contribution to
the proposed MAS. I shall conclude by drawing some more general lessons
about 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 ac-
knowledge the widespread instrumental use of MAS. Many computer scientists