Artificial Intelligence in MOBA Games: A Multivocal Literature Mapping

Lincoln Magalhães Costa, Anders Drachen*, Francisco Carlos Monteiro Souza, Geraldo Xexéo

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


Esports - games played competitively - comprise a major sector of the global games industry. Esports has been used as a testbed for game 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 DOTA 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 languageEnglish
JournalIEEE Transactions on Games
Publication statusE-pub ahead of print - 2023
Externally publishedYes


  • Artificial Intelligence
  • Bibliographies
  • Databases
  • Games
  • Industries
  • Literature Mapping
  • Machine Learning
  • Machine learning
  • Measurement
  • Multiplayer Online Battle Arena
  • Systematics


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