Klassische Themen der Computerwissenschaft 3 VO, 1 UE, 716.113 / 716.114 Bernhard Aichernig Oswin Aichholzer Alexander Felfernig Gerald Steinbauer Franz Wotawa Institut für Softwaretechnologie, TU Graz Inffeldgasse 16b, 2.Stock 1
Allgemeine Infos LV-Zeiten: VO: Mittwoch 11:45-14:00 HS i11 (Beginn 11:50) UE: Mittwoch 18:00-18:45 HS i11 (bzw nach Vereinbarung) Webseite: http://www.ist.tugraz.at/ktdcw10.html tugraz at/ktdcw10 html Zu VO / UE im TUGOnline anmelden (Frist 15.Okt). Ohne Anmeldung kein Zeugniss! 2
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Prüfung Gesamtprüfung über alle Themenblöcke Termin am Semesterende: Montag 31.01.2011 13:00-15:00, i13 Weitere Termine später, je nach Bedarf 4
Vorläufiger Zeitplan 06.10.2010 11:45-12:30 HS i11, Vorbesprechung I 13.10.2010 11:45-14:00 HS i11, VO O. Aichholzer 20.10.2010 11:45-14:00 HS i11, VO O. Aichholzer 18:00-18:45 HS i11, UE O. Aichholzer 27.10.2010 2010 11:45-14:00 HS i11, VO B. Aichernig 18:00-18:45 HS i11, UE O. Aichholzer 03.11.2010 11:45-14:00 HS i11, VO B. Aichernig 18:00-18:45 HS i11, UE B. Aichernig 10.11.2010 11:45-14:00 HS i11, VO A. Felfernig 18:00-18:45 HS i11, UE B. Aichernig 17.11.201011 11:45-14:00 HS i11, VO A. Felfernig 18:00-18:45 HS i11, UE A. Felfernig 24.11.2010 11:45-14:00 HS i11, VO F. Wotawa 18:00-18:45 HS i11, UE A. Felfernig 01.12.2010 11:45-14:00 HS i11, VO F. Wotawa 18:00-18:45 HS i11, UE F. Wotawa 08.12.2010 2010 Feiertag 15.12.2010 11:45-14:00 HS i11, Reservetermin 18:00-18:45 HS i11, UE F. Wotawa 12.01.2011 11:45-14:00 HS i11, VO G. Steinbauer 18:00-18:45 HS i11, Reservetermin 19.01.2011 11:45-14:00 HS i11, VO G. Steinbauer 18:00-18:45 HS i11, UE G. Steinbauer 26.01.2011 12:00-14:00 HS i11, Reservetermin 18:00-18:45 HS i11, UE G. Steinbauer 31.01.2011 13:00-15:00 HS i13, Prüfungstermin (Achtung: Übungstermine werden angepasst!) 5
Überblick 1 (Aichholzer) Game theory is a rather classical topic in mathematics and computer science. We will discuss the theory about numbers and nimbers and see how to (optimal) play the chocolate game, NIM, Kayles and other classical known (and unknown) games. In the exercise part of the lecture you will develop a program which can play several thousands of mathematical games optimally. 6
Überblick 2 (Steinbauer) Situation Calculus is a dialog of the first order logic for representing chances in a dynamic world in a formal way. All changes are the results of actions. The state of the world is represented by situations. The key feature of the SC is that it is based on logic and therefore all tools for logic can be use. Therefore, SC allows to reason about actions, change and situation, to make proofs or to plan. The SC is not only a theoretical construct. There exist implementation like the program language Golog which can be used to program and control real systems like robots. 7
Überblick 3 (Aichernig) Theory of Programming: A theory of programming explores the principles that underlie the successful practise of software engineering. In this part of the course we introduce different mathematical techniques for describing programs and show how they relate. We cover specifications and their stepwise refinement, as well as denotational, algebraic and operational semantics. 8
Überblick 4 (Felfernig) Constraint Programming (CP): CP is one of the closest approaches computer science has yet made to the Holy Grail of programming: the user states the problem, the computer solves it. [Freuder 1997] CP is used in many application areas such as configuration or scheduling. In this part of the course we will discuss major approaches to represent and solve constraint satisfaction problems (CSPs). The major goals are (1) to get an understanding of the basic formal properties of CSPs and (2) to be able to represent realworld problems as a corresponding CSP. 9
Überblick 5 (Wotawa) Artificial Intelligence (AI): AI is one large and active research area in computer science. Building intelligent t systems that t interact t with other intelligent t entities are of particular interest. In my part of the lecture I'll Ill talk about special aspects of knowledge representation and reasoning. In particular I'll focus on non-monotonic reasoning and its application to diagnosis. i The objectives of this part are (1) to get an impression about the state of the art in AI, (2) to get knowledge about open research issues, and (3) to understand how to represent and use knowledge to fulfill an intelligent task, i.e., fault detection and localization. 10