Human-Agent Teamwork in Cyber Operations: Supporting Co-evolution of Tasks and Artifacts with Luna

Abstract. In this article, we outline the general concept of coactive emergence, an iterative process whereby joint sensemaking and decision-making activities are undertaken by analysts and software agents. Then we explain our rationale for the development of the Luna software agent framework. In particular, we focus on how we use capabilities for comprehensive policy-based governance to ensure that key requirements for security, declarative specification of task-work, and built-in support for joint activity within mixed teams of humans and agents are satisfied

Implementing collective obligations in human-agent teams using KAoS policies

Obligations can apply to individuals, either severally or collectively. When applied severally, each individual or member of a team is independently responsible to fulfill the obligation. When applied collectively, it is the group as a whole that becomes responsible, with individual members sharing the obligation. In this paper, we present several variations of common teamwork models involving the performance of collective obligations. Some of these rely heavily on a leader to ensure effective teamwork, whereas others leave much room for member autonomy. We strongly focus on the implementation of such models. We demonstrate how KAoS policies can be used to establish desired forms of cooperation through regulation of agent behavior. Some of these policies concern invariant aspects of teamwork, such as how to behave when a leader is present, how to ensure that actions are properly coordinated, and how to delegate actions. Other policies can be enabled or disabled to regulate the degree of autonomy of the team members. We have implemented a prototype of a Mars-mission scenario that demonstrates varying team behavior when applied across these different teamwork models. © Springer-Verlag Berlin Heidelberg 2010

Contrasting Cases: A Strategy for Advanced Learning Using Simulation-based Training

Scenario-based training (SBT) as a medium for facilitating higher order or advanced learning has not been exploited fully. This paper argues for the use of contrasting cases to facilitate advanced learning within practice environments, where advanced learning is characterized by well differentiated and organized knowledge that can be generalized and abstracted. The rationale and guidance for incorporating contrasting cases into SBT is provided. A learning framework is leveraged to further describe how the method of contrasting cases can be adapted to address the challenges of learners at different stages of skill acquisition

Coactive Design: Designing Support for Interdependence in Joint Activity

Coactive Design is a new approach to address the increasingly sophisticated roles that people and robots play as the use of robots expands into new, complex domains. The approach is motivated by the desire for robots to perform less like teleoperated tools or independent automatons and more like interdependent teammates. In this article, we describe what it means to be interdependent, why this is important, and the design implications that follow from this perspective. We argue for a human-robot system model that supports interdependence through careful attention to requirements for observability, predictability, and directability. We present a Coactive Design method and show how it can be a useful approach for developers trying to understand how to translate high-level teamwork concepts into reusable control algorithms, interface elements, and behaviors that enable robots to fulfill their envisioned role as teammates. As an example of the coactive design approach, we present our results from the DARPA Virtual Robotics Challenge, a competition designed to spur development of advanced robots that can assist humans in recovering from natural and man-made disasters. Twenty-six teams from eight countries competed in three different tasks providing an excellent evaluation of the relative effectiveness of different approaches to human-machine system design.Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc