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. Emotion is critical for the flexible, intelligent behavior of biological organisms. Accordingly, multiple attempts to model emotion in robots and artificial agents have been described in the last decades. Yet, how emotion is modeled and how it interfaces with "cognitive architectures" remains poorly developed.