NEMO - A Neural, Emotional Architecture for Human-AI Teaming

In this work, we propose a novel architecture for agents to be employed in Human-AI Teaming in various, even critical, domains based upon affective computing, empathy, and Theory of Mind, and a description of the user profile and the operational, professional, and ethical requirements of the domain in which the agent operates. In this paper, we outline the architecture’s building blocks and their interconnections. The architectural design agent encompasses a Knowledge Graph to enclose the above-mentioned kinds of knowledge and a Behavior Tree enhanced via a Neural component, where the latter elaborates sensor input from devices that monitor the user and input from the knowledge graph. The enhanced behavior tree actually interacts with the user, making actions or providing suggestions, and returns feedback to feed to the knowledge graph as a novelty in the literature. We briefly present a case study, on which to experiment once the implementation, which is presently at an initial stage, will be completed. We discuss in some detail the Prolog program implementing the behavior tree, and discuss why we chose Prolog.