Formalizing Distributed Situation Awareness in Multi-Agent Networks

Abstract

The version of distributed situation awareness (DSA) used in this article originated in human factors/ergonomics. Typically, this has involved the study of human operators working in teams and has used various forms of concept maps to qualitatively describe the information that team members use. In this article, we apply the concept of DSA to multi-agent teams (where team members might be human or automation) and extend the concept using the formal properties of Bayesian belief networks. In particular, we show how the Bayesian belief network can define DSA and how such a network can (using expectation maximization) adapt, even on the basis of limited information. The approach was considered in terms of situation awareness levels of perception (i.e., sensor state values conversion to belief) and projection (in terms of prediction and mission missing values estimation accuracy).