Trends in combat technology research point to an increasing role for uninhabited vehicles and other robotic elements in modern warfare tactics. However, real-time control of multiple uninhabited battlefield robots and other semi-autonomous systems, in diverse fields of operation, is a difficult problem for modern warfighters that, while identified, has not been adequately addressed.
Soar Technology is applying software agent technology to simplify demands on the human operator. Our goal is to build intelligent systems capable of finding the best balance of control between the human and autonomous system capabilities. We are developing an Intelligent Control Framework (ICF) from which to create agent-based systems that are able to dynamically delegate responsibilities across multiple robotic assets and the human operator. This paper describes proposed changes to our ICF architecture based on principles of human-machine teamwork derived from collaborative discourse theory. We outline the principles and the new architecture, and give examples of the benefits that can be realized from our approach.
This paper describes a system for implementing adjustable autonomy levels in simulated unmanned vehicles using an approach based upon the fields of deontics and Joint Intention Theory (JIT). It discusses Soar Technology's Intelligent Control Framework research project (ICF), the authors' use of deontics in the creation of adjustable autonomy for ICF, and some possible future directions in which the research could be expanded. Use of deontics and JIT in ICF has allowed us to define system-wide formal limits on the behavior of the unmanned systems controlled by ICF, to increase the flexibility of our adjustable autonomy system, and to decrease the granularity of the autonomy adjustments. This set of formalisms allows the unmanned system maximal autonomy in the default case, while allowing the user and supervisory agents to constrain that autonomy in situations when necessary. Unlike more strictly layered adjustable autonomy formalisms, our adjustable autonomy formalism can be used to restrict subsets of autonomous behaviors, rather than entire systems, in response to situational requirements.