Cognitive computing for coalition situational understanding

Preece, Alun David ORCID: https://orcid.org/0000-0003-0349-9057, Cerutti, Federico ORCID: https://orcid.org/0000-0003-0755-0358, Braines, David, Chakraborty, Supriyo and Srivastava, Mani 2017. Cognitive computing for coalition situational understanding. Presented at: IEEE Smart World Congress 2017 Workshop: DAIS 2017 - Workshop on Distributed Analytics InfraStructure and Algorithms for Multi-Organization Federations, San Francisco, CA, USA, 7-8 August 2017.

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Abstract

The term cognitive computing (CC) refers to computer systems that harness multiple techniques from artificial intelligence (AI) and signal processing (SP). Situational understanding (SU) involves creating and reasoning about models of an environment and events. Coalition operations are defined by multiple partners seeking to achieve a common purpose. This paper characterises the SU problem in a coalition operations context — coalition situational understanding (CSU) — in terms of a set of problem attributes. The paper argues that CSU problems require CC system solutions involving a hybrid of AI and SP approaches. The paper outlines some of the architectural choices for CC CSU systems.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Completion
Status:	Unpublished
Schools:	Computer Science & Informatics Crime and Security Research Institute (CSURI)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Related URLs:	Organisation
Date of First Compliant Deposit:	11 June 2017
Last Modified:	02 Nov 2022 11:15
URI:	https://orca.cardiff.ac.uk/id/eprint/101355

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