Franziska Klügl-Frohnmeyer

Learn More
In this paper we present analysis and calibration techniques that exploit knowledge about a multi agent society in order to calibrate the system parameters of a corresponding society simulation model. The techniques address typical problems of multi agent simulation calibration like the vast amount of parameters that need to be calibrated, the complex(More)
In modern societies the demand for mobility is increasing daily. Hence, one challenge to researchers dealing with traffic and transportation is to find efficient ways to model and predict traffic flow, even if the behaviour of people in traffic is not a trivial problem. Increasingly more people travel longer distances and choose more complex routes and(More)
1. Motivation The SeSAm (Shell for Simulated Agent Systems) provides a generic environment for modeling and experimenting with agent-based systems. We specially focused on providing a framework for the easy construction of complex models. Although the idea of a domain-independent multi-agent simulation environment is not new, none of the existing(More)
In this paper, we present the most important features of SeSAm, a modeling and simulation platform for multi-agent simulations. Based on a declarative, explicit model representation and visual programming, it allows implementing models on specification level. Optimizing compilation allows efficient simulation of the explicit model representation. It was(More)
In this paper we want to show the possibilities to use agent-based modeling and simulation for software development. Therefore we present the integrated environment SeSAm and recent extensions, that allow creating simulated environments for agent based software as well as actually developing and deploying software agents.
Modeling and simulating complex natural systems is a demanding task. With multi-agent simulation a rather new modeling and simulation method is available that is based on a set of interacting autonomous agents. However, designing a multi-agent simulation is very effortful due to the increased amount of parameters of the model. Thus a modeler has to be sure(More)
Multi-Agent Simulation can be seen as simulated multi-agent systems situated in a simulated environment. Thus, in simulations the modelled environment should always be a first order object that is as carefully developed as the agents themselves. This is especially true for evolutionary simulation and simulation of adaptive multi-agent systems, as the agents(More)