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.

2024S, VU, 2.0h, 3.0EC
TUWEL

Course evaluation

Properties

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

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 constraint 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

Topics:

  • Basic Concepts
  • Uninformed Search Strategies  
  • Heuristic Algorithms
  • Constraint Satisfaction Problems
  • Constraint Programming Techniques
  • Modeling CSP 
  • 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

Immanent

Additional information

The preliminary discussion/first lecture will take place on 05.03.2024 (15:15 - 16:45)

 

 

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

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue15:00 - 17:0005.03.2024 - 25.06.2024FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue15:00 - 17:0012.03.2024 - 25.06.2024Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Problem Solving and Search in Artificial Intelligence - Single appointments
DayDateTimeLocationDescription
Tue05.03.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue12.03.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue12.03.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue19.03.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue19.03.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue09.04.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue09.04.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue16.04.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue16.04.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue23.04.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue23.04.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue30.04.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue30.04.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue07.05.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue07.05.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue14.05.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue14.05.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue28.05.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures
Tue28.05.202415:00 - 17:00FAV Hörsaal 1 Helmut Veith - INF Lectures
Tue04.06.202415:00 - 17:00Seminarraum FAV 01 C (Seminarraum 188/2) Lectures

Examination modalities

Assessment

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

Open book exam.

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Tue15:00 - 17:0025.06.2024 FAV Hörsaal 1 Helmut Veith - INFassessed09.06.2024 15:00 - 24.06.2024 17:00TISSFinal exam
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
17.01.2024 10:00 11.03.2024 12:00 18.03.2024 18:00

Registration modalities

Ort: TISS

Curricula

Literature

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

Language

English