181.190 Problem Solving and Search in Artificial Intelligence
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020S, VU, 2.0h, 3.0EC


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise

Learning outcomes

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


Subject of course


  • 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)


Teaching methods

  • 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


Mode of examination


Additional information

The preliminary discussion (and the first lecture) will take place on 02.03.2020 (12:15 - 14:00) (

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



Course dates

Mon12:00 - 14:0002.03.2020 - 09.03.2020FAV Hörsaal 1 Helmut Veith - INF Lecture
Problem Solving and Search in Artificial Intelligence - Single appointments
Mon02.03.202012:00 - 14:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Mon09.03.202012:00 - 14:00FAV Hörsaal 1 Helmut Veith - INF Lecture

Examination modalities


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


DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Mon17:00 - 19:0014.10.2024FAV Hörsaal 1 Helmut Veith - INF assessed04.07.2024 12:00 - 07.10.2024 14:00TISSProblem Solving and Search in AI (second exam..)

Course registration

Begin End Deregistration end
01.12.2019 10:00 08.03.2020 23:00 09.03.2020 17:00

Registration modalities




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 paper

Slides: TUWEL


Accompanying courses