This paper is concerned with the question to which extent a change in the selective pressure might improve the runtime of an optimization algorithm considerably. The subject of this examination is the class of symmetric functions, i.e. OneMax with a subsequent application of a real valued function. We consider an improvement in runtime as considerable if an exponential runtime becomes polynomial. The basis for this examination is a Markov chain analysis. An exact criterion for static selective pressure, telling which functions are solvable in polynomial time, is extended to a sufficient (but not necessary) criterion for changing selection pressure.

Modern computer games place different and more diverse demands on the behavior of non-player characters in comparison to computers playing classical board games like chess. Especially the necessity for a long-term strategy conflicts often with game situations that are unsteady, i.e. many non-deterministic factors might change the possible actions. As a consequence, a computer player is needed who might take into account the danger or the chance of his actions. This work examines whether it is possible to train such a player by evolutionary algorithms. For the sake of controllable game situations, the board game Kalah is turned into an unsteady version and used to examine the problem.

Der Origamistern bietet zahlreiche Möglichkeiten für mathematische und informatische Fragestellungen. In diesem Artikel werden verschiedene Färbungsprobleme des Origamisterns diskutiert. Abschließend wird kurz dargestellt, wie sich die Behandlung des Origamisterns im fächerverbindenden Unterricht einbetten lässt.

Allein schon die Anzahl der Beiträge in diesem Band zum 65. Geburtstag von Volker Claus und ihre so unterschiedliche Thematik weist auf die Breite seines Wirkens und die Anerkennung hin, die er in sei

The class of symmetric functions is based on the OneMax function by a subsequent assigning application of a real valued function. In this work we derive a sharp boundary between those problem instances that are solvable in polynomial time by the Metropolis algorithm and those that need at least exponential time. This result is both proven theoretically and illustrated by experimental data. The classification of functions into easy and hard problem instances allows a deep insight into the problem solving power of the Metropolis algorithm and can be used in the process of selecting an optimization algorithm for a concrete problem instance.

Beim Erstellen von Bildungsstandards ebenso wie bei der individuellen Schwerpunktsetzung als Lehrender in der Informatikausbildung stellt sich die Frage, wie gut dabei getroffene Entscheidungen tatsachlich sind. In diesem Beitrag werden Bewertungsformen vorgestellt und anhand eines Beispiels aus der Hochschullehre diskutiert.

Up to now there is no standardized strategy in how to teach evolutionary algorithms. Surely the answer to this question depends on the teaching context and the target group. But in the field of scientific teaching it is essential to abstract from paradigm orientation to a more general concept of evolutionary computing and to the underlying foundation. At the University of Stuttgart we pursue this aim with a very theoretically oriented lecture, a seminar, and a year-long study project. The lecture aims at an understanding of the working principles of evolutionary algorithms. In the seminar the students shall generate a comprehensive view through own presentations and conducted discussions. In the project an evolutionary algorithm is applied to a real world problem by a group of 6 to 10 students.