攻击规划领域理论的自动构建

Xiaochen Li, W. Mao, D. Zeng, Fei-Yue Wang
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引用次数: 18

摘要

恐怖组织正在设计越来越复杂的袭击计划。潜在恐怖分子模仿或构建袭击计划的能力可以帮助我们了解恐怖活动背后的意图和动机。人工智能中的规划技术是一种可行的计算方法。传统的人工智能规划方法依赖于由领域专家手工编制的预定义领域理论。为了方便领域理论的构建和规划的生成,提出了一种从自由文本数据中自动构建领域理论的方法。我们提出的方法的有效性通过使用真实世界的恐怖主义计划的实验研究进行了实证评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic construction of domain theory for attack planning
Terrorism organizations are devising increasingly sophisticated plans to conduct attacks. The ability of emulating or constructing attack plans by potential terrorists can help us understand the intents and motivation behind terrorism activities. A feasible computational method to construct plans is planning technique in AI. Traditionally, AI planning methods rely on a predefined domain theory which is compiled by domain experts manually. To facilitate domain theory construction and plan generation, we propose a method to construct domain theory automatically from free text data. The effectiveness of our proposed approach is evaluated empirically through experimental studies using real world terrorist plans .
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