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Technologies of Video Games

Code 11498
Year 1
Semester S2
ECTS Credits 6
Workload PL(30H)/T(30H)
Scientific area Informatics
Mode of delivery Face-to-face.
Work placements N/A.
Learning outcomes Objectives of the Course Unit:
- To enable students to have a holistic vision of computing through video games.
- To enable students to develop skills in innovation, design and development of game engines, including its data structures and algorithms.

Learning outcomes of the course unit:
At the end of this course unit a student should be able to:
- Use a game engine to build a game.
- Implement, test and embed an algorithm in a game sub-engine, either a geometry sub-engine, or in an artificial intelligence sub-engine, or in a sub-engine concerning physics and collision of bodies, etc.
- Make a critical analysis of an algorithm relative to a given game technology, and, thereafter, be able to sketch an innovative algorithm or a set of hypotheses that could lead to innovative technologies and / or algorithms for games.
Syllabus - Introduction, planning, and project.
- Game genres.
- Architecture of game engines.
- Object data structures.
- Scene graph and management.
- Spatial data structures.
- Culling.
- Terrain generation and modelling.
- Motion and collisions.
- Collision detection/resolution.
- Game physics.
- Path finding.
- Steering behaviors and crowds.
- Game networking.
Main Bibliography - D. Eberly. 3D Game Engine Architecture. Morgan Kaufmann Publishers, 2005.
- D. Eberly. 3D Game Engine Design. Morgan Kaufmann Publishers, 2007.

Further Bibliography:
- A. Watt and F. Policarpo. 3D Games: Real-time Rendering and Software Technology (vol.1). Addison-Wesley Publ. Company, 2000.
- A. Watt and F. Policarpo. 3D Games: Animation and Advanced Real-time Rendering (vol.2). Addison-Wesley Publ. Company, 2003.
- T. Akenine-Moller and E. Haines. Real-Time Rendering. A.K. Peters, 2002.
- D. Eberly. Game Physics. CRC Press, 2010.
- Christer Erikson. Real-time Collision Detection. The Morgan Kaufmann Series in Interactive 3-D Technology, CRC Press, 2004.
- Ian Millington and John Funge. Artificial Intelligence for Games. CRC Press, 2009.
- Mat Buckland. Programming Game AI by Example. Wordware Publishing Inc., 2004.
- Jouni Smed and Harri Hakonen. Algorithms and Networking for Computer Games. John Wiley & Sons, 2006.
Planned learning activities and teaching methods - Theoretical classes in which one challenges students to present their ideas and solutions to the problems posed by the teacher.
- Practical laboratory classes in which students are led to develop algorithms learned in lectures.
- Follow-up tutorial whenever students need it to develop their projects or to consolidate their knowledge.
- An individual project serves above all to develop an algorithm out of a game engine, but each student is then required to integrate it into an engine developed by the teacher and collaborators;
as an alternative to a complete project of a game, each student may opt by developing and implementing 3 algorithms built on a 3D basic scene.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2017-07-01

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