Formal Interpretation of a Multi-Agent Society As a Single Agent

In this paper the question is addressed to what extent the collective processes in a multi-agent society can be interpreted as single agent processes. This question is answered by formal analysis and simulation. It is shown for an example process how it can be conceptualised, formalised and simulated in two different manners: from a single agent (or cognitive) and from a multi-agent (or social) perspective. Moreover, it is shown how an ontological mapping can be formally defined between the two formalisations, and how this mapping can be extended to a mapping of dynamic properties. Thus it is shown how collective behaviour can be interpreted in a formal manner as single agent behaviour.Collective Intelligence, Simulation, Logical Formalisation, Single Vs. Multi-Agent Behaviour

Does This Suit Me? Validation of Self-modeling Network Models by Parameter Tuning

In this chapter it is discussed how a personalised temporal-causal network model can be obtained that fits well to specific characteristics of a person, and his or her connections and further context. A model is an approximation, but always a form of abstraction of a real-world phenomenon. Its accuracy and correctness mainly depend on the chosen abstracting assumptions and the personal and contextual (network) characteristics defining the model. Depending on the complexity of the model, the number of its characteristics can vary from just a couple to thousands. These network characteristics usually represent specific features or properties of the modelled phenomenon, for example, for modelling human processes personality traits or social interaction properties. No values for such characteristics are given at forehand. From a more general and abstract view, they can be considered parameters of the model. Estimation of such parameters for a given model is a nontrivial task. In this chapter, it is discussed how this can be addressed for temporal-causal network models based on the parameter tuning method of Simulated Annealing and a specific component within the dedicated modeling environment, thereby making use of MATLAB’s built-in optimser Optimtool.</p

Being an emigrant

Panel: Loyalty and Betraya

Modelling conflict management in design: an explicit approach

This paper focusses on how conflicts that arise during a design process and the management of conflicts can be modelled. A number of possible conflict types are distinguished and it is described how each of them can be detected during the design process, using an explicit meta-representation. Furthermore, it is shown how these conflict types can be analyzed and managed by means of strategic meta-knowledge about design processes. © 1995, Cambridge University Press. All rights reserved