Catálogo de publicaciones - libros

The emergence of order in systems with many actors or agents is an interesting problem for sociology as well as for computer science. Starting the from sociological theory of the dyadic “situation of double contingency”, our main focus is on large actor populations and their capability to produce order depending on different actors’ constellations. Based on the theory for dyadic actor constellations we present our model of the actor. We do not want the actors to identify one another, so we do not need to modify this model if we scale up population size next and introduce constellations. Thereby we take regular, random and small–world constellations into account. After describing our measures of order we study emergence of order in different constellations for varying population sizes. By means of simulation experiments we show that systems with small–worlds exhibit highest order on large populations which gently decreases on increasing population sizes.

In the absence of pre-established coordination structures, what can a self-governed entity—i.e. an entity that chooses on its own between its possible actions and cannot be controlled externally—do to evoke another self-governed entity’s cooperation? In this paper, the motivating conditional self-commitment is conceived to be the basic mechanism to solve coordination problems of this kind. It will be argued that such commitments have an inherent tendency to become more and more generalized and institutionalised. The sociological concept of generalized symbolic media is reinterpreted as a concept that focuses on this point. The conceptual framework resulting from the considerations is applicable to coordination problems between human actors as well as to coordination problems between artificial agents in open multi-agent systems. Thus, it may help to transfer solutions from one realm to the other.

Internet communication is a major challenge for anyone claiming to design scalable multiagent systems. Millions of messages are passed every day, referring to one another and thus shaping a gigantic network of communication. In this paper, we compare and discuss two different approaches to modelling and analysing such large-scale networks of communication: Social Network Analysis (SNA) and Communication-Oriented Modelling (COM). We demonstrate that, with regard to scalability, COM offers striking advantages over SNA. Based on this comparison, we identify mechanisms that foster scalability in a broader sense, comprising issues of downscaling as well.

It is widely accepted in Distributed Artificial Intelligence that a crucial property of artificial agents is their . Whereas agent autonomy enables features of agent-based applications like flexibility, robustness and emergence of novel solutions, autonomy might be also the reason for undesired or even chaotic agent behavior, and unmanageable system complexity. As a conceptual approach to the solution for this “autonomy dilemma” of agent-based software engineering, this work introduces the framework for open multiagent systems based on special meta-agents, so-called . Instead of restricting agent autonomy by means of normative constraints and defined organizational structures as usual, Mirror-Holons allow for the gradual of agent interaction and system functionality. Their main purpose is the derivation and adaption of and evolving stochastical from the observation and compilation of agent communication and additional design objectives. Social programs can either be executed by the Mirror-Holons themselves, or communicated to the agents and the system designer, similar to the functionality of mass media like television or newspapers in human societies.

This paper introduces (CS) as a unified model for socially intelligent systems. This model derived from sociological systems theory, combines the empirical analysis of communication in a social system with logical processing of social information to provide a general framework for computational components that exploit communication processes in multiagent systems. We present an elaborate formal model of CS that is based on expectation networks and their processing. To illustrate how the CS layer can be integrated with agent-level expectation-based methods, we discuss the conversion between CS and interaction frames in the InFFrA architecture. A number of CS-based applications that we envision suggest that this model has the potential to add a new perspective to Socionics and to multiagent systems research in general.