Model-Based Systems & Qualitative Reasoning (MQM)
Prof. Dr. Peter Struss
About
The Model-based Systems and Qualitative Reasoning Group of Professor Peter Struss works on developing knowledge and model-based systems for industrial or scientific applications.
Our main focus are modeling techniques based on first principles as well as problem solving algorithms. For further information check our
MQM Website.
Systems for automated fault analysis, diagnosis, testing, and repair of technical systems
The group has developed tools and applications dedicated to supporting diagnosis of real physical system. This includes the automated generation of diagnostic hypotheses, proposed tests and repair actions. This is done based on a component-oriented behavior model of the respective device. Models are also used to support activities during design, such as diagnosability analysis, sensor placement, and Failure Mode Effect Analysis (FMEA), a method used for the identification of potential error types and their effects on the examined object and to classify them with respect to criticality or diagnosability. In the framework of several European and national projects, we have been collaborating with other academic partners and companies, in particular with car industries. Ref. Struss, P.: Modellbasierte Systeme und Qualitative Modellierung. Erschienen in: Görz, G., Rollinger, C., Schneeberger, J. (Hrsg.): Handbuch der Künstlichen Intelligenz, 3. Auflage, Oldenbourg Verlag, München, 2000.
Model-based behavior prediction, situation assessment and therapy proposal for natural and technical processes, in particular ecological systems
In complex ecosystems, it is often a knowledge intensive task to infer the causes of undesirable developments. One has to know possible phenomena and their preconditions. Assessing the situation of an ecosystem from a limited number of observations can be defined as a challenging diagnosis task. Additionally, one wants to reason about possible cures or symptom treatments in order to influence the ecosystem in a direction that is in accordance with some specified goals. We have developed theoretical foundations and systems for such an extended diagnosis task and apply the results to water treatment problems. Project AGUA
Automated and qualitative modeling
Many tasks, for example in diagnosis or during early stages of design, have to be performed without precise numerical information, and sometimes, our knowledge about functional interdependencies underlying a class of systems (e.g. ecosystems) is partial and qualitative. We develop and apply methods and systems for representing and reasoning with incomplete knowledge about physical systems. Qualitative modeling aims at representing all possible behaviors consistent with the given partial knowledge. In order to be applicable within industrial application systems, modeling itself has to be supported and automated. This includes the automated composition of models from model fragments (“compositional modeling? and the automated generation of qualitative models from numerical models.
People
More information can be found
here.
Principal Investigators
Researchers
Student Researchers
Guest Researchers
Alumni
- Alessandro Fraracci, PhD?
- Martin Sachenbacher, PhD?
- Ulrich Heller, PhD?
- Andreas Malik, PhD?
- Jakob Mauss, PhD?
Teaching
More information can be found
here.
Courses WS 2016/17
- Automated Problem Solving in Artificial Intelligence
- Knowledge-based Systems for Industrial Applications
Courses SS 2015
- Knowledge-based Systems for Industrial Applications
Courses WS 2014/15
- Environmental Modeling and Decision Support Systems
- Modelling and Knowledge Representation in Artificial Intelligence
Courses SS 2014
- Knowledge-based Systems for industrial Applications
- Automated Problem Solving
Courses WS 2013/14
- Environmental Modeling and Decision Support Systems
Publications
Read our
MQM Publication List.