Supporting Reasoning with Different Types of Evidence in Intelligence Analysis [Conference Paper]

NESL Technical Report #: 2015-3-2


Abstract: The aim of intelligence analysis is to make sense of information that is often conflicting or incomplete, and to weigh competing hypotheses that may explain a situation. This imposes a high cognitive load on analysts, and there are few automated tools to aid them in their task. In this paper, we present an agent-based tool to help analysts in acquiring, evaluating and interpreting information in collaboration with others. Agents assist analysts in reasoning with different types of evidence to identify what happened and why, what is credible, and how to obtain further evidence. Argumentation schemes lie at the heart of the tool, and sensemaking agents assist analysts in structuring evidence and identifying plausible hypotheses. A crowdsourcing agent is used to reason about structured information explicitly obtained from groups of contributors, and provenance is used to assess the credibility of hypotheses based on the origins of the supporting information.

Publication Forum: ACM International Conference on Autonomous Agents and Multiagent Systems (AAMAS) , 9 pages , ACM , May 2015.

Page (Count): 9

Date: 2015-05-01

Publisher: ACM

Public Document?: Yes

NESL Document?: Yes

Document category: Conference Paper