Biological computing (or biocomputing) offers potential advantages over silicon-based
computing in terms of faster decision-making, continuous learning during tasks, and greater …

Disasters can have devastating impacts on communities and economies, underscoring the
urgent need for effective strategic disaster risk management (DRM). Although Artificial …

Computational autonomy has begun to receive significant attention, but neither the theory
nor the physics is sufficiently able to design and operate an autonomous human-machine …

Abstract Machine Learning (ML) techniques offer exciting new avenues for leadership
research. In this paper we discuss how ML techniques can be used to inform predictive and …

Because in military situations, as well as for self-driving cars, information must be processed
faster than humans can achieve, determination of context computationally, also known as …

Utilizing big data and artificial intelligence technologies, we developed the Collaborative
Structure Search Framework (CSSF) algorithm to analyze students' learning paths from real …

For the science of autonomous human–machine systems, traditional causal-time
interpretations of reality in known contexts are sufficient for rational decisions and actions to …

As humanity grapples with the concept of autonomy for human–machine teams (A-HMTs),
unresolved is the necessity for the control of autonomy that instills trust. For non-autonomous …

Abstract Systems Engineering (SE) based test and evaluation (T&E) approaches have
proven crucial for successful realization of most modern‐day complex systems and system …

Explainability has emerged as a critical AI research objective, but the breadth of proposed
methods and application domains suggest that criteria for explanation vary greatly. In …