MAT-75006 Artificial Intelligence, 7 cr

Lisätiedot

No lectures during 2016-2017. Next implementation round: Spring 2018.
Suitable for postgraduate studies. Ei toteuteta lukuvuonna 2016-2017.

Vastuuhenkilö

Tapio Elomaa

Opetus

Toteutuskerta Periodi Vastuuhenkilö Suoritusvaatimukset
MAT-75006 2016-01 - Tapio Elomaa

Osaamistavoitteet

After completing the course the student will have be familiar with different areas of artificial intelligence. In particular, the student is able to apply to problems arising in application fields the basic methods of solving problems by searching, informed search and exploration, inference in first-order logic, probabilistic reasoning, learning from observations, and statistical learning methods. The student will be able to identify the computational complexity of the used technique. The student will obtain a deeper knowledge on the topic of the chosen study and presentation. Also hands-on experience on some specific artificial intelligence technique will be gathered in a programming home work.

Sisältö

Sisältö Ydinsisältö Täydentävä tietämys Erityistietämys
1. Logic, knowledge, and reasoning  propositional and first-order logic  knowledge bases 
2. Problem solving and search  heuristic search  algorithm A* 
3. Uncertain knowledge and reasoning  probabilistic reasoning  decision making 
4. Machine learning  learning from observations  statistical learning 

Ohjeita opiskelijalle osaamisen tasojen saavuttamiseksi

The course grade will be based on the course exam, a study/presentation, and programming home work. Active participation to weekly exercises yields extra points. If the student demonstrates thorough understanding of the core content, s/he may pass the course with grade 3. In order to achieve grade 4, the student must also demonstrate competency in complementary knowledge. The student may achieve grade 5, if s/he also demonstrates good command of specialist knowledge. If there are minor shortcomings regarding the core content, the student may receive the grade 1 or 2, depending on the number of flaws. If there are significant shortcomings regarding core content, the student will not pass the course.

Arvosteluasteikko:

Numerical evaluation scale (0-5)

Osasuoritukset:

Completion parts must belong to the same implementation

Oppimateriaali

Tyyppi Nimi Tekijä ISBN URL Lisätiedot Tenttimateriaali
Book   Artificial Intelligence: A Modern Approach   Stuart Russell & Peter Norvig         Yes   

Esitietovaatimukset

Opintojakso P/S Selite
MAT-02500 Todennäköisyyslaskenta Advisable    
MAT-02650 Algoritmimatematiikka Advisable    
TIE-02100 Johdatus ohjelmointiin Mandatory    
TIE-02200 Ohjelmoinnin peruskurssi Advisable    



Vastaavuudet

Opintojakso Vastaa opintojaksoa  Selite 
MAT-75006 Artificial Intelligence, 7 cr OHJ-2556 Artificial Intelligence, 6 cr  

Päivittäjä: Ikonen Suvi-Päivikki, 13.04.2016