Supporting Agile User Fusion Analytics through Human-Agent Knowledge Fusion

Abstract

For many types of data and information fusion, input from human users is essential, both in terms of defining or adjusting the processing steps, as well as in interacting with, understanding, and communicating the results. In many cases, information fusion should increase understanding for the human user(s) working as part of a team of interacting agents, taking into account the needs of each user type, and the factors that might affect individual and team performance. This paper focuses on the decision support that could be provided to users, by presenting a candidate environment to support comprehensive information fusion and exchange in support of human-agent knowledge fusion (HAKF). The paper outlines two distinct HAKF use cases of (1) foraging data for open source intelligence analysis, and (2) sensemaking fusion from sensors and machine agents, using Cogni-sketch. In the first use case, a traditional open source intelligence gathering exercise demonstrates information gathered from multiple sources and maps it to a common model of sensemaking. The second use case shows machine-led activities including fusion of machine vision and object identification, and the utilization of human-led semantic definitions of events and situations in support of sensemaking.