Abstract
In this paper, we take the first step towards building comprehensive bots capable of playing a simplified version of League of Legends, a popular 5v5 online multiplayer game. We implement two different agents, one using Reinforcement Learning and the other via Supervised Long Short Term Memory Network. League of Legends provides a partially observable game environment with an action space much larger than games like Chess or Go. Source code and demonstrations can be found at https://github.com/csci-599-appliedml-for-games/league-of-legends-bot.
Cite
CITATION STYLE
Lohokare, A., Shah, A., & Zyda, M. (2020). Deep learning bot for league of legends. In Proceedings of the 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2020 (pp. 322–324). The AAAI Press. https://doi.org/10.1609/aiide.v16i1.7449
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