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A Multicriteria Intelligence Aid Methodology Using MCDA, Artificial Intelligence, and Fuzzy Sets Theory

机译：使用MCDA，人工智能和模糊集理论的多准则情报援助方法论

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摘要

Intelligence is increasingly relevant today in both military and business intelligence contexts. Business executives, military, and governments have more large datasets and meet difficulties in anticipating threat/competitor future decisions. Decision anticipation is desirable because it will enhance situation understanding and then will limit the surprise effect and favor more appropriate reactions and decision-making. Generating and evaluating competitor/threat actions is a very challenging problem because of the uncertainty, incompleteness, and ambiguity associated with it. This paper extends the multicriteria decision aid (MCDA) methodology to the context of intelligence analysis and proposes the main pillars of a novel methodology called "Multicriteria Intelligence Aid" (MCIA). More specifically, this paper addresses how can we adapt MCDA to the context of intelligence analysis and how can we use existent methods and techniques from MCDA, artificial intelligence, and fuzzy sets theory to build this methodology. The paper presents the MCIA steps, which consist of (i) structuring the competitor/threat decision problem, (ii) handling imperfect data, (iii) modeling the analyst's risk attitude, and (iv) aggregating the performance of the generated potential actions. An illustration of the methodology is provided in the military context. Results show that the novel methodology is applicable and provides interesting and valuable results.
机译：如今，情报在军事和商业情报环境中都越来越重要。业务主管，军事人员和政府拥有更多的数据集，并且在预测威胁/竞争对手的未来决策时遇到困难。决策预期是可取的，因为它将增强对情况的理解，然后将限制意外影响，并支持更适当的反应和决策。产生和评估竞争对手/威胁行为是一个非常具有挑战性的问题，因为与之相关的不确定性，不完整性和模糊性。本文将多准则决策辅助（MCDA）方法扩展到了情报分析的背景，并提出了一种称为“多准则情报援助”（MCIA）的新颖方法的主要支柱。更具体地说，本文探讨了如何使MCDA适应智能分析的环境，以及如何利用MCDA，人工智能和模糊集理论中的现有方法和技术来构建这种方法。本文介绍了MCIA的步骤，包括（i）构建竞争对手/威胁决策问题，（ii）处理不完善的数据，（iii）对分析人员的风险态度进行建模，以及（iv）汇总所产生的潜在行为的绩效。在军事方面提供了该方法的说明。结果表明，该新方法是适用的，并提供了有趣且有价值的结果。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第10期|9281321.1-9281321.10|共10页
  • 作者

    Frini Anissa;

  • 作者单位

    Univ Quebec Rimouski, Sci Gest, Campus Levis, Levis, PQ, Canada;

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