Learning and reasoning in complex coalition information environments: a critical analysis

F Cerutti, M Alzantot, T Xing, D Harborne… - 2018 21st …, 2018 - ieeexplore.ieee.org
2018 21st International Conference on Information Fusion (FUSION), 2018ieeexplore.ieee.org
In this paper we provide a critical analysis with metrics that will inform guidelines for
designing distributed systems for Collective Situational Understanding (CSU). CSU requires
both collective insight-ie, accurate and deep understanding of a situation derived from
uncertain and often sparse data and collective foresight-ie, the ability to predict what will
happen in the future. When it comes to complex scenarios, the need for a distributed CSU
naturally emerges, as a single monolithic approach not only is unfeasible: it is also …
In this paper we provide a critical analysis with metrics that will inform guidelines for designing distributed systems for Collective Situational Understanding (CSU). CSU requires both collective insight-i.e., accurate and deep understanding of a situation derived from uncertain and often sparse data and collective foresight-i.e., the ability to predict what will happen in the future. When it comes to complex scenarios, the need for a distributed CSU naturally emerges, as a single monolithic approach not only is unfeasible: it is also undesirable. We therefore propose a principled, critical analysis of AI techniques that can support specific tasks for CSU to derive guidelines for designing distributed systems for CSU.
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