Potential flows for controlling scout units in StarCraft

K. Nguyen, Zhe Wang, R. Thawonmas
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引用次数: 9

Abstract

Real-Time Strategy (RTS) games typically take place in a war-like setting and are accompanied with complicated game play. They are not only difficult for human players to master, but also provide a challenging platform for AI research. In a typical RTS game, such as StarCraft, WarCraft, or Age of Empires, knowing what the opponent is doing is a great advantage and sometimes an important key to win the game. For that, good scouting is required. As subsequent work for improving the scouting agent in our StarCraft AI bot-IceBot-the winner of the mixed division in Student StarCraft AI Tournament 2012, this paper proposes a method that applies potential flows to controlling scout units in StarCraft. The proposed method outperforms an existing scouting method as well as a modified version of this existing method and is comparable to scouting by human players.
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《星际争霸》中控制侦察单位的潜在流程
即时战略(RTS)游戏通常发生在类似战争的背景下,并伴随着复杂的游戏玩法。它们不仅对人类玩家来说很难掌握,而且为人工智能研究提供了一个具有挑战性的平台。在典型的RTS游戏中,如《星际争霸》、《魔兽争霸》或《帝国时代》,知道对手在做什么是一大优势,有时甚至是赢得游戏的关键。为此,良好的侦察是必要的。为了改进我们的《星际争霸》AI机器人——冰机器人(2012年《星际争霸》学生AI锦标赛混合赛区冠军)的侦察代理,本文提出了一种应用潜在流来控制《星际争霸》侦察单位的方法。所提出的方法优于现有的球探方法以及该方法的改进版本,并且可与人类球员的球探相媲美。
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