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Complex Reflexive Agents As Models of Social Actors 1 the Socionics Initiative

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Complex Reflexive Agents As Models of Social Actors 1 the Socionics Initiative 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 ¯rst 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 arti¯cial actors (e.g., software agents). See (MÄuller, Malsch, and Schulz-Schae®er 1998) for an introductory text. The original focus of socionics was on the ¯rst 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 bene¯cial 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 de¯nition 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 view of scalability is also compatible with the view of scalability in computer science. Of course it is not obvious whether social systems are scalable or not. But we think that they are scalable to a certain extent, but how scalable they are is unknown and in our opinion an interesting research question. Today, in the socionics initiative, the transfer from social science to computer and vice versa is about equally weighted. So in addition to technical advances we can also see advances in the development of social theories by incorporating techniques from computer science. Now we will describe briefly the eight projects of the socionics initiative. Detailed information and recent pubilcations can be found on their web sites (see Sect. 1.9). 1.1 Behavior in Social Contexts - A Socionical Approach of Model Creation and Theory Evaluation Project manager: Prof. Dr. Rolf v. LÄude, Dr. Daniel Moldt, Prof. Dr. RÄudiger Valk The central method applied in this project are petri nets. Petri nets have been developed in computer science as a a formal, graphical, and executable technique for the speci¯cation and analysis of concurrent, discrete-event dynamical systems (Petri 1962). An elementary petri net consists of places and transitions connected by arcs. A place can hold a token. During a synchronous, deterministic update step tokens can move through transitions from one place to another, if the condition of the respective transition is ful¯lled. A large variety of petri nets exists. A variant developed by (Valk 1998) allows petri nets to become tokens of other petri nets. These hierarchical petri nets are used to build multi-agent architecture to model social systems. The architecture has been applied to develop a middle range theory for decision processes in organizations. A concrete simulation model has been built for a decision process in a university. A second focus of the project is the formalization and comparison of social theories using petri nets as formal tools. The advantage of petri nets is that they can be easily designed using standard computer software and that the formal representation of a petri net is equivalent to a graphical representation. This means that after designing a petri net graphically on a computer, it can be simulated without any additional e®ort. 1.2 The Emergence and Modi¯cation of Social Structure in Groups of Intel- ligent, Multiply-Motivated, Emotional Agents Project manager: Prof. Dr. Dietrich DÄorner, Prof. Dr. Paul Levi The starting point of this project is a model of an simulated autonomous agent called \PSI". The agent has been designed following psychological theory. The control mechanism consists of various symbolic (rule based) and sub-symbolic layers (e.g., arti¯cial neural networks). Multiple goals, cognition, emotions, and self-observation are already formalized within PSI's architecture. Now, PSI is extended by social motives in order to study their impact on cooperation and group structure. 1.3 INKA: Integration of Cooperative Agents in Complex Organizations Project manager: Prof. Dr. Hans-Dieter Burkhard, Prof. Dr. Werner Rammert 2 The aim of the INKA project is to develop foundations for open agent-based systems which are able to cope with incoherence and heterogeneity in complex organizations. The real world prototype application domain is a clinical planing system. The resulting multi-agent system should be able to schedule the various medical treatments in a hospital in cooperation with human users. 1.4 Conflict Handling and Structural Change : Social Theory as \Construc- tion Manual" for Adaptive Multi-Agent Systems (ConStruct) Project manager: Prof. Dr. Wilfried Brauer, Dr. Gerhard WeiÄs, Prof. Dr. Thomas Malsch The1 primary goals of the project are the improvement of the design process and the e±ciency of multiagent systems with the help of sociologically founded models, and the construction of new architectures for very large adaptive "arti¯cial societies" modelled after modern human society. Doing so, concepts of learning and conflict from distributed arti¯cial intelligence (DAI) are brought together with concepts from sociology. This approach especially aims at the devel- opment of novel methods for the software design and the programming of multiagent systems, contributing to the emerging ¯eld of Agent-Oriented Software Engineering (AOSE). Two di®erent architectures are developed which arise from two competing sociological paradigms: (1) Pragmatism and symbolic interactionism, and (2) Niklas Luhmanns autopoietic systems theory (Luhmann 1984). From these contrary sociological views on the interrelation between conflict and structure, two competing models of arti¯cial sociality are derived: (1) a model of self-determined change via the creative resolution of action conflicts and (2) a model of "evolutionary di®erentiation of social systems as a di®erentiation of conflicts” (Luhmann 1984). These models respectively the architectures based on them are concretized and evaluated by real- world application scenarios. Systems for the semantical rating of web sites through competing agents and the agent-based linkage of web pages have already been speci¯ed and are being implemented. 1.5 Models of Social Organization in DAI and Sociology: Analyzing the Habitus-Field- Theory with a View of its Transferability on Software Architecture and Concepts of DAI Project manager: Dr. Klaus Fischer, Prof. Dr. JÄorg Siekmann, Dr. Michael Florian In this project the focus is on robustness of multi-agent systems. The approach is inspired by research in Sociology on social order, e.g., the reproduction of structure in a society of actors despite the dynamics of interaction. The theoretical basis forms the recent habitus-¯eld theory by Pierre Bourdieu (Bourdieu 1987). The main concepts used in the approach are task delegation and social delegation, modes of delegation and types of organizations. These new concepts are applied to a concrete application domain, namely transportation systems where transportation jobs are traded and delegated and social factors like trust plays an important role. 1.6 Structural Di®erentiation in Multi-Agent-Systems Project manager: Prof. Dr. Werner Dilger, Prof. Dr. Bernhard Giesen 1Text copied and slightly modi¯ed from: http://wwwbrauer.in.tum.de/gruppen/kikog/projects/socionics/ 3 The aim of the project is to build a multi-agent system which allows to study environmental conditions which lead to the emergence of a symbolic communication system with coordina- tive functionality. This means that in the model a symbol system can emerge through some kind of evolutionary process and that the emerged symbol system is used to coordinate action. Practically, in the multi agent system communication and action is coupled such that agents have to communicate successfully ¯rst in order to achieve a successful coordinated action. Only successful coordinated actions lead to a gain of a certain type of energy, which is required for an agent's reproduction, which in turn leads to an evolutionary (reproductive) advantage for communicating agents and possibly to the emergence of a communication system.
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