论文标题
预期的反计划
Anticipatory Counterplanning
论文作者
论文摘要
在竞争环境中，通常代理试图防止对手实现目标。以前的大多数防止方法都认为对手的目标是先验的。其他人只有一旦推断出对手的目标就开始执行动作。在这项工作中，我们介绍了一种新型与域无关的算法，称为预期反计划。它将对手目标的推理与计划中心群的计算结合了推论，以在对手目标未知的问题中产生主动的反策略。实验结果表明，这种新技术的表现如何优于反应性反计划，增加了阻止对手实现其目标的机会。
In competitive environments, commonly agents try to prevent opponents from achieving their goals. Most previous preventing approaches assume the opponent's goal is known a priori. Others only start executing actions once the opponent's goal has been inferred. In this work we introduce a novel domain-independent algorithm called Anticipatory Counterplanning. It combines inference of opponent's goals with computation of planning centroids to yield proactive counter strategies in problems where the opponent's goal is unknown. Experimental results show how this novel technique outperforms reactive counterplanning, increasing the chances of stopping the opponent from achieving its goals.
