Universität Wien FIND

052212 VU Gaming Technologies (2019W)

Continuous assessment of course work

Registration/Deregistration

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Thursday 03.10. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 10.10. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 17.10. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 24.10. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 31.10. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 07.11. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 14.11. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 28.11. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 05.12. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 12.12. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 09.01. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 16.01. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 23.01. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
Thursday 30.01. 13:15 - 14:45 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG

Information

Aims, contents and method of the course

Basics of real-time physics engines and AI engines for computer games. Weekly tasks and the game project are implemented using a game engine.

Assessment and permitted materials

Weekly tasks and a semester project.

Minimum requirements and assessment criteria

Basi knowledge in programming. Final grading is computed according to:
--All individual tasks and the semester project are graded
--Final grading is due to weighted sum S of gradings of weekly tasks and game
--Individual tasks have an overall weight of 70%
--Final computer game has a weight of 30%, must be shown to instructor in person!
--Positive ONLY if computer game works!
--Final grading due to weighted sum S:
S>90% : Sehr Gut (1)
S>80% : Gut (2)
S>70% : Befriedigend (3)
S>59% : Genügend (4)
S<60% Nicht Genügend (5)

Examination topics

Game physics: rigid body physics,, collision detection and response
Game AI: movement, path finding, decision making

Reading list

David H. Eberly, Game Physics, CRC Press; 2 edition (April 5, 2010)
Christer Ericson, Real-Time Collision Detection, CRC Press (December 22, 2004)

Association in the course directory

Module: GD2 GAT

Last modified: Mo 23.09.2019 14:07