"Honor of Kings Arena: an Environment for Generalization in Competitive" by Hua Wei, Jingxiao Chen et al.
 

Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning

Document Type

Conference Proceeding

Publication Date

1-1-2022

Abstract

This paper introduces Honor of Kings Arena, a reinforcement learning (RL) environment based on Honor of Kings, one of the world's most popular games at present. Compared to other environments studied in most previous work, ours presents new generalization challenges for competitive reinforcement learning. It is a multi-agent problem with one agent competing against its opponent; and it requires the generalization ability as it has diverse targets to control and diverse opponents to compete with. We describe the observation, action, and reward specifications for the Honor of Kings domain and provide an open-source Python-based interface for communicating with the game engine. We provide twenty target heroes with a variety of tasks in Honor of Kings Arena and present initial baseline results for RL-based methods with feasible computing resources. Finally, we showcase the generalization challenges imposed by Honor of Kings Arena and possible remedies to the challenges. All of the software, including the environment-class, are publicly available at: https://github.com/tencent-ailab/hok_env. The documentation is available at: https://aiarena.tencent.com/hok/doc/.

Identifier

85148465686 (Scopus)

ISBN

[9781713871088]

Publication Title

Advances in Neural Information Processing Systems

ISSN

10495258

Volume

35

Grant

62076161

Fund Ref

AIDS Institute

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