Deep Learning Bot for League of Legends

Authors

  • Aishwarya Lohokare University of Southern California
  • Aayush Shah University of Southern California
  • Michael Zyda University of Southern California

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-applied-ml-for-games/league-of-legends-bot.

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Published

2020-10-01

How to Cite

Lohokare, A., Shah, A., & Zyda, M. (2020). Deep Learning Bot for League of Legends. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 16(1), 322-324. Retrieved from https://ojs.aaai.org/index.php/AIIDE/article/view/7449