Complex Reflexive Agents as Models of Social Actors Peter Dittrich (1,3) and Thomas Kron (2) (1) University of Dortmund, Department of Computer Science, D-44221 Dortmund, Germany (2) University of Hagen, Department of Sociology, D-58084 Hagen, Germany (3) Friedrich-Schiller-University Jena, Department of Mathematics and Computer Science, and Jena Centre for Bioinformatics, D-07743 Jena, Germany Abstract The first part gives an overview about the socionics initiative which has been established by the German Research Foundation (DFG) about three years ago. In this initiative eight project cooperating in a tandem-structure with at least one partner from Computer Science and one from Sociology in each ”tandem project”. The second part focuses on our own project where the central metaphor is ”the complex agent”. We present latest results from two lines of research we are following: (1) An architecture to build “realistic” agents for modeling social actors. (2) Models of learning and reflexive agents. In this line of research we have developed a model which uses genetic programming (GP) as a learning mechanism, and a model of the ”situation of double contingency” introduced by Luhmann as an explanation for the origin of social order where learning and reflexivity plays an important role. 1 The Socionics Initiative The socionics initiative has been established by the German Research Foundation (DFG) about three years ago. In this initiative eight project cooperating in a tandem-structure with at least one partner from Computer Science and one from Sociology in each ”tandem project”. Socionics aims on the one hand at developing computer technologies by employing paradigms of our social world, on the other hand computer science techniques are used to develop and validate social theories. A third aspect of socionics is the study of hybrid systems which consist of real social actors (e.g., humans) and artificial actors (e.g., software agents). See (M¨ uller, Malsch, and Schulz-Schaeffer 1998) for an introductory text. The original focus of socionics was on the first and third aim, namely, to build technical systems with the aid of Sociology. This motivation has also led to the name “socionics”, which has been derived in a similar way as the name “bionics”. Why is it beneficial to look a social systems in order to build technical systems? Obviously social systems show how a huge number of autonomous actors are integrated into a quite complex system, which is able to perform a variety of simple and complex tasks. In addition, a social system can have a set of properties that we also desire from technical systems, such properties are for example: robustness, stability, adaptability, flexibility, creativity, and scalability. Scalability has been a central matter of the socionics initiative, recently. Although there is no common definition to which all eight socionics projects would agree we can roughly say that a (social) system is scalable if its identity and performance would not decrease drastically when we increase the number of components (e.g., members, actors, or agents) of the system. This 1