Learning and Reasoning in Complex Coalition Information Environments: A Critical Analysis
| Autor: | Ramya Raghavendra, Mani Srivastava, Moustafa Alzantot, Supriyo Chakraborty, Jonathan Z. Bakdash, Murat Sensoy, Tianwei Xing, Alun Preece, Lance M. Kaplan, Angelika Kimmig, Daniel Harborne, Federico Cerutti, Dave Braines |
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| Rok vydání: | 2018 |
| Předmět: |
QA75
artificial intelligence for situational understanding collective situational understanding critical analysis of artificial intelligence techniques Computer science 02 engineering and technology 010501 environmental sciences 01 natural sciences Data science 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Situational ethics 0105 earth and related environmental sciences |
| Zdroj: | FUSION Fusion 2018: 21st International Conference on Information Fusion |
| Popis: | In this paper we provide a critical analysis with met- rics 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. |
| Databáze: | OpenAIRE |
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