Schedule of Lectures, Workshops, and Tutorials on Computation of Explanations

1. University of Alabama, Huntsville
May 3 and 4, 2007
For details go to UAH Workshop


Four lectures discuss key elements of a new technique for constructing simple explanations from numerical data. Applications arise in many areas such as bioinformatics, economics, engineering, finance, and medicine.

Particular focus is on the very difficult situation where comparatively few data records with numerous data elements per record are given.

The workshop makes use of the following material: The book "Design of Logic-based Intelligent Systems" by K. Truemper (Wiley, 2004), and the technical paper "Obtaining Explanations from Numerical Data" by K. Riehl and K. Truemper.

The technique has been implemented in the explanation modules of the Leibniz System software . The workshop covers the use of that software.

Schedule of Lectures, Workshops, and Tutorials on Intelligent Systems

1. Institute IASI-CNR, Rome, Italy
Week June 7-11, 2004
For details contact [email protected]

2. University of Cologne, Cologne, Germany
Week September 6 - 10, 2004
For details contact [email protected]

3. Institute ZIB, Berlin, Germany
Week September 27 - October 1, 2004
For details contact [email protected]. Here is the Workshop Schedule

4. Technical University, Munich, Germany
September 19, 2005
For details contact [email protected]

5. University of Cologne, Cologne, Germany
September 27, 2005
For details contact [email protected]

6. Technical University, Munich, Germany
March 8, 2006
For details contact [email protected]


An intelligent system is a system that accomplishes tasks that, when carried out by people, require significant intelligence. Example tasks are medical diagnosis, processing of natural language, and supervision of complex processes.

The lectures cover the design and implementation of intelligent systems that are based on an extension of propositional logic. The lectures do not assume any prior knowledge of logic.

Topics of lectures:

- Levels of thinking such as thinking about problems (1st level) and thinking about thinking (2nd level)
- Expert systems and intelligent agents as special cases of intelligent systems
- Logic techniques such production rules, Prolog, propositional logic, first-order logic, fuzzy logic, Bayesian networks
- Propositional logic with extensions
- Problems SAT and MINSAT
- Theorem proving
- Uncertainty of statements and conclusions
- Learning logic from data, including transformation of rational data and set data to logic data
- Logic problems at the second level of the polynomial hierarchy
- Question-and-answer processes
- Systems that construct systems, which are examples of thinking about thinking