Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage...

After successful completion of the course, students are able to:

- Develop and apply uninformed and informed search methods

- Design and implement (meta)heuristic methods for various problems

- Model problems with constrsint programming (CP) modeling languages and SAT

- Use CP/SAT for solving various problems

- Understand concepts regarding tree/hypertree decompositions and be able to use (hyper)tree decompositions in problem solving

- Explain methods that are used for automated algorithm configuration and algorithm selection

- Apply automated algorithm selection and configuration for various problems/algorithms

Topics:

• Basic Concepts
• Uninformed Search Strategies  
• Heuristic Algorithms
• Constraint Satisfaction Problems
• Constraint Programming Techniques
• Decomposition Techniques (Tree and Hypertree Decompositions)
• Metaheuristic Algorithms (Simulated Annealing, Tabu Search, Genetic Algorithms¿)
• Adversarial Search and Game Playing
• Application of Machine Learning in Search (Automated Algorithm Selection, Hyperheuristics)
• Algorithm Configuration (Automated Parameter Tuning)

Didactical Concept

• Lectures
• Exercises/project: students will implement an exact or a metaheuristic method for a particular problem
• Discussion for solving of different logical problems and puzzles
• Presentation of solution methods from students
• Demonstration of applications developed in research and industrial projects of our group

• Lectures
• Exercises/project: students will implement an exact or a metaheuristic method for a particular problem
• Discussion for solving of different logical problems and puzzles
• Presentation of solution methods from students
• Demonstration of applications developed in research and industrial projects of our group

The preliminary discussion (and the first lecture) will take place on 02.03.2020 (12:15 - 13:00) (FAV Hörsaal 1, Favoritenstr. 9-11, Erdgeschoß)

 ECTS Breakdown:

9 classes (including preparation): 25 h

project (including presentation): 25 h

exam: 25 h

---------------

total: 75 h

For latest information, please visit TUWEL

Assessment

• Written exam(60%)
• Assignments (Project) (40%)

Ort: TISS

Z. Michalewicz and D. B. Fogel. How to Solve It: Modern Heuristics, 2nd edition, Springer-Verlag, 2004

Artificial Intelligence: A Modern Approach (Third Edition) by Stuart Russell and Peter Norvig; Prentice Hall, 2010.

Different scientific papers

Slides: TUWEL