Prof. Dr. Holger Giese


What does Informatics offer for Modeling and Analysis of Complex Systems?

Talk by Prof. Dr. Holger Giese.

When: 14.10.2009, 10.00 Uhr
Where: Max Planck Institute of Molecular Plant Physiology



Informatics approaches complex, information processing systems and their underlying principles. Even though it addresses only information processing systems, the results may be of interest also to other disciplines as nowadays in many of them such as physics or biology information plays an increasingly important role. In this talk we will provide a sketch of some of the results for modeling and analysis of complex systems achieved in informatics. We will in particular review some concepts and technologies that are promising also for modeling and analysis of complex systems which go beyond informatics.

In order to master complexity, informatics tries to describe systems as simple as possible by means of models formulated in appropriate languages. Hence, numerous specific languages, core concepts for “good” languages, technologies for the efficient definition of languages and technologies for automatically deriving tools for those languages have been developed. In other disciplines appropriate modeling languages and tools also play an important role when it comes to modeling and analysis and thus some of these results may be of interest: Numerous modeling concepts for specific kind of systems that reflect the specific restrictions present have been developed. The spectrum reaches from simple, discrete automata to complex, compositional models which cover the complex interplay of subsystem with respect to interaction, structural changes as well as creation or deletion of subsystems. In addition powerful analysis techniques have been developed. It exist several examples where such modeling concepts and analysis techniques have been successfully employed for non informatics problems such as, for example, gene assembly. Furthermore, there exist approaches in informatics which allow to incrementally developing a complete model by means of partial models. Separate observations can be step-wise captured by partial models and the complex, complete model is than automatically derived. The modeling of complex cellular processes is one example for the successful application of such approaches.

Informatics has on the other hand also been stimulated by other disciplines. The current trend to address the ever increasing complexity of informatics systems by adapting phenomena which can be observed for complex systems in nature fall into this category. The resulting ideas how to model and analyze self-organizing software systems, self-optimizing software systems and (self-)adaptive software systems provide further interesting connection points between informatics and other disciplines. Furthermore, often the modeling concepts of a single discipline are not sufficient when complex systems are addressed which require the expertise of different disciplines. Multi-Paradigm Modeling approaches the resulting problem of integrating different modeling languages at the different levels semantics/mathematics, syntax and technology. Examples are complex hybrid models which result from the combination of continuous models for physical parts and discrete models for the information processing part.