
Proceedings Paper
Investigating immersive collective intelligenceFormat | Member Price | Non-Member Price |
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Paper Abstract
Collective intelligence is generally defined as the emergence and evolution of intelligence derived from the collective and collaborative efforts of several entities; to include humans and (dis)embodied intelligent agents. Recent advances in immersive technology have led to cost-effective tools that allow us to study and replicate interactions in a controlled environment. Combined together, immersive collective intelligence holds the promise of a symbiotic intelligence that could be greater than the sum of the individual parts. For the military, where the decision making process is typically characterized by high-stress and high-consequence, the concept of a distributive, immersive collective intelligence capability is game changing. Commanders and staff will now be able to remotely immerse themselves in their operational environment with subject matter expertise and advanced analytics. This paper presents the initial steps to understanding immersive collective intelligence with a demonstration designed to discern how military intelligence analysts benefit from an immersive data visualization.
Paper Details
Date Published: 10 May 2019
PDF: 9 pages
Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 110060U (10 May 2019); doi: 10.1117/12.2519364
Published in SPIE Proceedings Vol. 11006:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
Tien Pham, Editor(s)
PDF: 9 pages
Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 110060U (10 May 2019); doi: 10.1117/12.2519364
Show Author Affiliations
Mark Mittrick, U.S. Army Research Lab. (United States)
John Richardson, U.S. Army Research Lab. (United States)
Mark Dennison Jr., U.S. Army Research Lab. (United States)
John Richardson, U.S. Army Research Lab. (United States)
Mark Dennison Jr., U.S. Army Research Lab. (United States)
Theron Trout, U.S. Army Research Lab. (United States)
Eric Heilman, U.S. Army Research Lab. (United States)
Timothy Hanratty, U.S. Army Research Lab. (United States)
Eric Heilman, U.S. Army Research Lab. (United States)
Timothy Hanratty, U.S. Army Research Lab. (United States)
Published in SPIE Proceedings Vol. 11006:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
Tien Pham, Editor(s)
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