Abstract
This paper reviews the field of Game AI, which not only deals with creating agents that can play a certain game, but also with areas as diverse as creating game content automatically, game analytics, or player modelling. While Game AI was for a long time not very well recognized by the larger scientific community, it has established itself as a research area for developing and testing the most advanced forms of AI algorithms and articles covering advances in mastering video games such as StarCraft 2 and Quake III appear in the most prestigious journals. Because of the growth of the field, a single review cannot cover it completely. Therefore, we put a focus on important recent developments, including that advances in Game AI are starting to be extended to areas outside of games, such as robotics or the synthesis of chemicals. In this article, we review the algorithms and methods that have paved the way for these breakthroughs, report on the other important areas of Game AI research, and also point out exciting directions for the future of Game AI.
Original language | English |
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Journal | KI - Künstliche Intelligenz |
Volume | 34 |
Issue number | 1 |
Pages (from-to) | 7-17 |
Number of pages | 11 |
ISSN | 0933-1875 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- Game AI
- Automated Game Content Generation
- Game Analytics
- Player Modelling
- AI Algorithms