Abstract
Esports - games played competitively - comprise a major sector of the global games industry. Esports have been used as a testbed for game artificial intelligence (AI) and game analytics for two decades. This article presents a multivocal literature mapping of available research that focuses strictly on the use of artificial intelligence approaches in multiplayer online battle arena (MOBA) games, one of the most popular esports genres and the one most widely used for game AI and game analytics research. A mapping is performed on relevant publications published between 2011 and 2022 and systematically examines them to extract similarities, gaps, and main findings. We analyzed 124 publications to identify the most studied topics, the most commonly used techniques, and the most commonly applied evaluation methods. The results show that League of Legends and Defense of the Ancients are the most studied games, with outcome prediction being the most popular research topic. Finally, we provide an analysis of the potential future flagship areas for research in the domain, considering the gaps found in the white and grey literature.
Original language | English |
---|---|
Journal | IEEE Transactions on Games |
Volume | 16 |
Issue number | 2 |
Pages (from-to) | 250-269 |
ISSN | 2475-1502 |
DOIs | |
Publication status | Published - Jun 2024 |
Keywords
- Artificial Intelligence
- Bibliographies
- Databases
- Games
- Industries
- Literature Mapping
- Machine Learning
- Machine learning
- Measurement
- Multiplayer Online Battle Arena
- Systematics
- literature mapping
- machine learning
- Artificial intelligence
- multiplayer online battle arena (MOBA)