Co-Arg: Cogent Argumentation with Crowd Elicitation
October 02, 2018 Β· Declared Dead Β· π arXiv.org
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Authors
Mihai Boicu, Dorin Marcu, Gheorghe Tecuci, Lou Kaiser, Chirag Uttamsingh, Navya Kalale
arXiv ID
1810.01541
Category
cs.AI: Artificial Intelligence
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
This paper presents Co-Arg, a new type of cognitive assistant to an intelligence analyst that enables the synergistic integration of analyst imagination and expertise, computer knowledge and critical reasoning, and crowd wisdom, to draw defensible and persuasive conclusions from masses of evidence of all types, in a world that is changing all the time. Co-Arg's goal is to improve the quality of the analytic results and enhance their understandability for both experts and novices. The performed analysis is based on a sound and transparent argumentation that links evidence to conclusions in a way that shows very clearly how the conclusions have been reached, what evidence was used and how, what is not known, and what assumptions have been made. The analytic results are presented in a report describes the analytic conclusion and its probability, the main favoring and disfavoring arguments, the justification of the key judgments and assumptions, and the missing information that might increase the accuracy of the solution.
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