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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.

2021S, VU, 2.0h, 3.0EC


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

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 and a metaheuristic/hybrid 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 will take place on 12.03.2021 (10:15 - 11:00) (Online). Lecture will take place online every Friday from 10:15-12:00.


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

Fri10:00 - 12:0012.03.2021 - 25.06.2021 Zoom (LIVE)Lectures
Problem Solving and Search in Artificial Intelligence - Single appointments
Fri12.03.202110:00 - 12:00 ZoomLectures
Fri19.03.202110:00 - 12:00 ZoomLectures
Fri26.03.202110:00 - 12:00 ZoomLectures
Fri16.04.202110:00 - 12:00 ZoomLectures
Fri23.04.202110:00 - 12:00 ZoomLectures
Fri30.04.202110:00 - 12:00 ZoomLectures
Fri07.05.202110:00 - 12:00 ZoomLectures
Fri21.05.202110:00 - 12:00 ZoomLectures
Fri28.05.202110:00 - 12:00 ZoomLectures
Fri04.06.202110:00 - 12:00 ZoomLectures
Fri11.06.202110:00 - 12:00 ZoomLectures
Fri18.06.202110:00 - 12:00 ZoomLectures
Fri25.06.202110:00 - 12:00 ZoomLectures

Examination modalities


  • Written exam(50%)
  • Assignments (Project) (50%)

Open book exam. The exam will take place online (via Zoom).


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
28.01.2021 10:00 16.03.2021 11:00 26.03.2021 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


Previous knowledge

Knowledge of algorithms and data structures

Programming skills



Accompanying courses