Evaluating a virtual human storyteller for improved decision support

Abstract

Defence and security organisations face increasing challenges to maximise the real-time integration of data and information for improved decision making. This is particularly true in applications of human-machine teaming. These teams create complex interaction environments for human operators that integrate autonomous systems, multi-modal displays, and information streams at differing temporal scales. Examples of these complex environments can be seen in simulation pilots operating in large scale synthetic training scenarios, and operators of multi-unmanned aerial vehicle (multi-UAV) systems. In both these cases, an individual must perform a primary task (directing simulated or real entity behaviour), whilst simultaneously following a pre-defined scenario plan. On top of this, emergent information, with varying levels of uncertainty, must be acted on or ignored as appropriate. Additional contextual information may also be required such that these actions can occur with an understanding of broader contextual factors. The efficiency with which this primary, planned, emergent, and contextual information is presented underpins decision support and superiority in increasingly complex military contexts. In this research, we evaluate the use of storytelling via a virtual human to deliver complex geo-spatial conflict briefing information.