FUSED REASONING UNDER UNCERTAINTY FOR SOLDIER CENTRIC HUMAN-AGENT DECISION MAKING

Abstract

As agents (devices and software) are increasingly incorporated into every aspect of our lives, the research area of human-agent teaming has seen an increase in attention. This is particularly true considering the varied, dynamic, and fast pace operations Soldiers are currently facing and will be facing in the future. There is a common idea that, in the future, the speed of machines will far exceed a Soldiers’ ability to react or even comprehend the complex activities of their digital teammates, which is a concern. Uncertainty in this accelerated environment will present unique and unforeseen challenges that may potentially inhibit a Soldier’s ability to make decisions effectively and to efficiently decide fast enough to support the future battlefield optempo. To accelerate decision making in Army operations the military is relying on agents and enabling technologies such as complex systems that integrate intelligent sensor networks and autonomous devices. These systems-of- systems will be driven by machine learning enabled artificial intelligence algorithms and will form teams with human warfighters, where both must act as one unit to accomplish their mission. Explanations can provide key information about the data or behavior of complex systems to the human to aide human agent teaming.