MOBA: a New Arena for Game AI

By Victor do Nascimento Silva, Luiz Chaimowicz. 2017

32 citations recorded by the source corpus.

Games have always been popular testbeds for Artificial Intelligence (AI). In the last decade, we have seen the rise of the Multiple Online Battle Arena (MOBA) games, which are the most played games nowadays. In spite of this, there are few works that explore MOBA as a testbed for AI Research. In this paper we present and discuss the main features and opportunities offered by MOBA games to Game AI Research. We describe the various challenges faced along the game and also propose a discrete model that can be used to better understand and explore the game. With this, we aim to encourage the use of MOBA as a novel research platform for Game AI.

Subfields: Artificial Intelligence, Reinforcement Learning

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Citations in the corpus

Deep Reinforcement Learning that Matters (2017, background): “…experienced dramatic growth in attention and interest due to promising results in areas like: controlling continuous systems in robotics (Lillicrap et al. 2015a), playing Go (Silver et al. 2016), Atari (Mnih et al. 2013), and competitive video games (Vinyals et al. 2017; Silva and Chaimowicz 2017).”
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning (2019, background): “As we know, RTS games are considered as a grand challenge for AI research (Vinyals et al. 2019; Silva and Chaimowicz 2017).”
Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings (2020, background): “, Dota, Honor of Kings, and League of Legends, have been considered as an important and suitable testbed for artificial intelligence (AI) research due to their considerable complexity and varied playing mechanics [1]–[4].”