Lehr- und Forschungseinheit für Datenbanksysteme
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Managing Massive Multiplayer Online Games (SS 2018)

News

  • Please register for the additional exam via Uniworx.
  • You can check your exam paper on 08.08.2018 from 2 p.m. until 3:30 p.m. s.t. in room 157, Oettingenstr. 67.
  • The additional exam takes place at 11.10. 2-4 p.m. (see details below).
  • Please read the guidelines for the exam
  • Please bring your Laptop to the today's (27.06.2018) tutorial.
  • Please register for the final exam via Uniworx.
  • The exam will be on Fr 27.7. 12:00-14:00.
  • The formula for movement under constant accelaration was corrected in the slides of chapter 3 and is now consistent with the tutorials.
  • The video of course can be found at here.
  • Registration in UNIWORX is open. register here

Organisation

  • Course: 3+2 hours weekly (equals 6 ECTS)
  • Lecture: Prof. Dr. Matthias Schubert
  • Assistant: Sebastian Schmoll
  • Beneficial: Lecture "Knowledge Discovery in Databases I" or "Machine Learning" or other data analytics methods
  • Audience: The course is directed towards master students in informatics and media informatics
  • Video lectures:The video of course can be found at here.

Time and Locations

All times are c.t. (cum tempore)

Component When Where Starts at
Lecture Tue, 13,00 - 16,00 h Room A 014 (HGB) 10.04.2018
Tutorial 1 Wed, 14,00 - 16,00 h Room D Z003 (HGB) 18.04.2018
Tutorial 2 Wed, 16,00 - 18,00 h Room D Z003 (HGB) 18.04.2018

Content

A massive multiplayer online game (MMOG) is a virtual environment which players visit for entertainment. It is often played by thousands of players at the same time and allows huge varieties of player interactions. The course treats questions of how to implement and design MMOGs in order to scale with the players while keeping the game experience on an interactive or even real-time level. This includes spatial management, client-server communication, persistency and consistences of virtual environments hosting the MMOG. A further important aspect of online games is monitoring the player experience and evaluate success strategies. This task is done by Game Analytics methods. Finally, the lecture gives an outlook on artifical intelligence which can be used to improve player interaction, develop challenging computer components or simply make the interaction with the virtual environment more interesting.

 

 

Course Schedule

LectureTutorial
DateTopicDateTopic
10.04.2018 Computer Games 11.04.2018 --
17.04.2018 Game Core (1) 18.04.2018 Time
24.04.2018 Game Core (2) 25.04.2018 Space (v1.1)
Solutions for 2-3
Announcement
01.05.2018 May Day 02.05.2018 Unsupervised Learning (v1.1)
Exercise
08.05.2018 Distributed Games 09.05.2018 Homework - Solution
Tutorial Exercise
15.05.2018 Persistence 16.05.2018 Homework (v1.1)
22.05.2018 Whit Tuesday 23.05.2018 Homework - solution
29.05.2018 Game Analytics 30.05.2018 Homework
Tutorial Exercise
05.06.2018 Game Analytics
Temporal Analytics
06.06.2018 Homework
Tutorial Exercise
12.06.2018 Spatial Analytics 13.06.2018 Homework
19.06.2018 Spatial Analytics (cont.)
Ranking Skill
20.06.2018 Homework - solution
26.06.2018 AI (part1) 27.06.2018 Homework - Solution
Tutorial Exercise (html) - Solution (ipynb, py, html)
03.07.2018 AI (part2) 04.07.2018 Homework
Tutorial Exercise
Slides
10.07.2018 Summary 11.07.2018 Homework - code
Solution (ipynb, html)

Final Examination

Date: Fr 27.7. 12:00-14:00
Location: Geschwister-Scholl-Platz 1, main building, room B 201
Please read the guidelines for the final exam

Additional Examination

Date: Thu 11.10. 14:00-16:00
Location: Geschwister-Scholl-Platz 1, main building, room M 218
Please register for the exam using uniworx!