Stress Propagation in Human-Robot Teams Based on Computational Logic Model

Mission teams are exposed to the emotional toll of life and death decisions. These are small groups of specially trained people supported by intelligent machines for dealing with stressful environments and scenarios. We developed a composite model for stress monitoring in such teams of human and autonomous machines. This modelling aims to identify the conditions that may contribute to mission failure. The proposed model is composed of three parts: 1) a computational logic part that statically describes the stress states of teammates; 2) a decision part that manifests the mission status at any time; 3) a stress propagation part based on standard Susceptible-Infected-Susceptible (SIS) paradigm. In contrast to the approaches such as agent-based, random-walk and game models, the proposed model combines various mechanisms to satisfy the conditions of stress propagation in small groups. Our core approach involves data structures such as decision tables and decision diagrams. These tools are adaptable to human-machine teaming as well.Comment: Submitted to IEEE Aerospace 2023 conferenc

Discovering Emerging Applications of Multi-Valued Logic: Protocols for Human-Autonomy Teaming

This paper discovers an emerging area of application of the advanced Multivalued Logic (MVL), – a collaboration between humans and autonomous machines in the first responder teams (firefighters, search-and-rescue operators, disaster response personnel, and military special operations forces). We developed an approach to formalization of the collaboration protocols (also known as contagion protocols) that model the human-machine teaming in emergency missions. MVL techniques satisfy the requirements of encoding the states of stress and trust, and their propagation between the teammates. Advanced MVL techniques are also useful for other applications, such as modeling the contagion of infection, or the spread of rumors, ideas, panic, and fear