Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

Motivations, Values and Emotions: 3 sides of the same coin

This position paper speaks to the interrelationships between the three concepts of motivations, values, and emotion. Motivations prime actions, values serve to choose between motivations, emotions provide a common currency for values, and emotions implement motivations. While conceptually distinct, the three are so pragmatically intertwined as to differ primarily from our taking different points of view. To make these points more transparent, we briefly describe the three in the context a cognitive architecture, the LIDA model, for software agents and robots that models human cognition, including a developmental period. We also compare the LIDA model with other models of cognition, some involving learning and emotions. Finally, we conclude that artificial emotions will prove most valuable as implementers of motivations in situations requiring learning and development

Emotion in Future Intelligent Machines

Over the past decades, research in cognitive and affective neuroscience has emphasized that emotion is crucial for human intelligence and in fact inseparable from cognition. Concurrently, there has been a significantly growing interest in simulating and modeling emotion in robots and artificial agents. Yet, existing models of emotion and their integration in cognitive architectures remain quite limited and frequently disconnected from neuroscientific evidence. We argue that a stronger integration of emotion in robot models is critical for the design of intelligent machines capable of tackling real world problems. Drawing from current neuroscientific knowledge, we provide a set of guidelines for future research in artificial emotion and intelligent machines more generally

From Imprinting to Adaptation: Building a History of Affective Interaction

We present a Perception-Action architecture and experiments to simulate imprinting—the establishment of strong attachment links with a “caregiver”—in a robot. Following recent theories, we do not consider imprinting as rigidly timed and irreversible, but as a more flexible phenomenon that allows for further adaptation as a result of reward-based learning through experience. Our architecture reconciles these two types of perceptual learning traditionally considered as different and even incompatible. After the initial imprinting, adaptation is achieved in the context of a history of “affective” interactions between the robot and a human, driven by “distress” and “comfort” responses in the robot

From Human to Robot Interactions: A Circular Approach towards Trustworthy Social Robots

Human trust research uncovered important catalysts for trust building between interaction partners such as appearance or cognitive factors. The introduction of robots into social interactions calls for a reevaluation of these findings and also brings new challenges and opportunities. In this paper, we suggest approaching trust research in a circular way by drawing from human trust findings, validating them and conceptualizing them for robots, and finally using the precise manipulability of robots to explore previously less-explored areas of trust formation to generate new hypotheses for trust building between agents.Comment: In SCRITA 2023 Workshop Proceedings (arXiv:2311.05401) held in conjunction with 32nd IEEE International Conference on Robot & Human Interactive Communication, 28/08 - 31/08 2023, Busan (Korea