Selected Topics in Artificial Intelligence and Robotics - Constraint-based Models and Algorithms in Artificial Intelligence
Veranstaltung: Vertiefungsvorlesung
Professor: Dr. Martin Sachenbacher
Betreuer: Paul Maier
Zeit, Ort: Dienstag, 10:00-11:30, MI 02.09.023, Beginn: 28.04.2009
Sprache: German or English
Modul: IN3150
Detailinformationen
Syllabus
- Modeling with constraints: Constraint satisfaction problems (CSPs), constraint optimization problems (soft CSPs), boolean constraints (SAT, QBF);
- Algorithms for constraint solving: Search, inference, hybrids of search and inference, look-back and look-ahead methods;
- Techniques for large constraint networks: Exploiting structure in real-world problems, structural decomposition, conflict learning, randomization and restart techniques;
- Applications and case studies: Constraint-based frequency allocation in cellular networks, constraint-based computing for flexible machine control software, programming of fault-aware autonomous systems, immobots
Dates
The first lecture will be held on April 28, 2009.
Literature
The following books and book chapters cover parts of the lecture:- Rina Dechter: Constraint Processing. Morgan Kaufmann, 2003
- Francesca Rossi, Peter Van Beek, Toby Walsh: Handbook of Constraint Programming. Elsevier, 2006
- Carla P. Gomes, Henry Kautz, Ashish Sabharwal, Bart Selman: Satisfiability Solvers. In: Handbook of Knowledge Representation, Elsevier Series on Foundations of Artificial Intelligence, Vol. 3, 2008. PDF
