ABSTRACT
Intelligence (DAI), looks for (new techniques and concepts to satisfy the requirements
demanded by the increasingly complex applications, e.g. Internet-Services. In the area of Social
Simulation several sociological concepts are used to describe the interplay of artificial agents
in a multi-agent world and to help in describing the architectures that have been
built to model this kind of Distributed Artificial Intelligence. Terms like “society”,
“organization”, “cooperation” or “conflict” are widely used but the image of an “socially”
behaving “agent” is often misleading. Instead of merely pointing out these limitations that
arise from such notions, Socionics starts to evaluate the power of using sociological
concepts and theories for the development of computer technologies and implementation
techniques. There are two main areas for which Socionics tries to develop new solutions
to existing problems by exploiting sociological concepts: the first is Multi-Agent Systems
(MAS) and the second is the growing area of Hybrid Systems (HS). From a sociological
point of view “[m]odern society offers a rich reservoir of paradigms for modeling multi-
agent systems, e.g. social role and cultural values, norms and conventions, social
movements and institutions, power and dominance distribution. Computer Science might learn
from the adaptability, robustness, scalability and reflexivity of social systems and use their
building blocks to come up with more powerful technologies” (Müller, Malsch & Schulz-
Schaeffer 1998). But the benefit of an interdisciplinary approach like Socionics is
bilateral. Sociology can profit from Computer Science by using DAI techniques as
simulation tools for validating and extending their sociological concepts and theories.
