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A Micromanagement Task Allocation System for Real-Time Strategy Games

机译：实时策略游戏的微管理任务分配系统

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摘要

Real-time strategy (RTS) game play is a combination of strategy and micromanagement. While strategy is clearly important, the success of a strategy can depend greatly on effective micromanagement. Recent years have seen an increase in work focusing on micromanagement in RTS AI, but the great majority of these works have focused on policies for individual units or very specific situations, while very little work has aimed to address the need for a broadly applicable structure for unit group coordination. This paper conceptualizes RTS group level micromanagement as a multiagent task allocation (TA) problem, and proposes the micromanagement task allocation system (MTAS) as a framework to bridge the gap between strategy and unit level micromanagement. MTAS fits into the common layered RTS AI structure, and can thus, in principle, be integrated into any existing system based on this layered structure. We describe the integration of MTAS into E323AI (an existing AI player for the spring RTS engine), and provide empirical results demonstrating that MTAS leads to statistically significant improvement in performance on the popular RTS game Balanced Annihilation.
机译：实时策略（RTS）游戏是策略和微观管理的结合。尽管策略显然很重要，但是策略的成功在很大程度上取决于有效的微观管理。近年来，针对RTS AI的微观管理的工作有所增加，但是这些工作中的绝大多数都集中在针对单个单位或非常特殊情况的政策上，而很少有工作旨在解决对RTS AI的广泛适用结构的需求。单位小组协调。本文将RTS组级微管理概念化为一个多代理任务分配（TA）问题，并提出了微管理任务分配系统（MTAS）作为弥合策略与单位级微管理之间差距的框架。 MTAS适合于通用的分层RTS AI结构，因此，原则上可以将其集成到基于该分层结构的任何现有系统中。我们描述了将MTAS集成到E323AI（用于弹簧RTS引擎的现有AI播放器）中的经验，并提供了经验结果，证明MTAS在流行的RTS游戏“平衡歼灭”上带来了统计上的显着改进。

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