Title
Context-Driven Proactive Decision Support for Hybrid Teams
Abstract
A synergy between AI and the Internet of Things (IoT) will significantly improve sense-making, situational awareness, proactivity, and collaboration. However, the key challenge is to identify the underlying context within which humans interact with smart machines. Knowledge of the context facilitates proactive allocation among members of a human-smart machine (agent) collective that balances autonomy with human interaction, without displacing humans from their supervisory role of ensuring that the system goals are achievable. In this article, we address four research questions as a means of advancing toward proactive autonomy: how to represent the interdependencies among the key elements of a hybrid team; how to rapidly identify and characterize critical contextual elements that require adaptation over time; how to allocate system tasks among machines and agents for superior performance; and how to enhance the performance of machine counterparts to provide intelligent and proactive courses of action while considering the cognitive states of human operators. The answers to these four questions help us to illustrate the integration of AI and IoT applied to the maritime domain, where we define context as an evolving multidimensional feature space for heterogeneous search, routing, and resource allocation in uncertain environments via proactive decision support systems.
Year
DOI
Venue
2019
10.1609/aimag.v40i3.4810
AI MAGAZINE
DocType
Volume
Issue
Journal
40
3
ISSN
Citations 
PageRank 
0738-4602
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Manisha Mishra1244.82
Pujitha Mannaru200.34
David Sidoti3184.90
Adam Bienkowski401.01
Lingyi Zhang5474.21
Krishna R. Pattipati650682.13