MOBA: a New Arena for Game AI
Victor do Nascimento Silva1 and Luiz Chaimowicz2 1V. N. Silva is with the Department of Computing Science, University of Alberta, Canada Chaimowicz is with the Department of Computing Science, Federal University of Minas Gerais, Brazil. work was partially supported by FAPEMIG and CNPq
Abstract
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.
中文速览
MOBA（多人在线战术竞技）游戏如《英雄联盟》《Dota 2》占据了全球近30%的在线游戏时长，却几乎没有被当作人工智能研究的测试平台，这与同为策略游戏的《星际争霸》形成了鲜明对比。为了填补这一空白，作者系统梳理了MOBA游戏对AI研究构成的核心挑战——从赛前的英雄选禁、开局阵容分配、兵线发育，到团队协作与博弈策略——并提出了一套离散化的游戏抽象模型，将复杂的动态游戏环境转化为更便于算法研究的形式化框架。研究表明，MOBA在局部微操、不完全信息、多智能体协作、对手建模等方面提供了远比传统RTS更丰富且更贴近现实的挑战场景。这项工作的意义在于：它为AI研究者指明了一个拥有海量真实玩家数据、极高社会影响力的新型测试平台，有望像《星际争霸》推动RTS领域一样，推动智能体决策与博弈研究迈上新台阶。
原文 arXiv:1705.10443;中英对照 + 大白话阅读 https://aha.fim.ai/paper/1705.10443v1