3 research outputs found
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
Personality affected robotic emotional model with associative memory for human-robot interaction
The decision making process in communication is affected by internal and external factors from dynamic environments. Humans can perform a variety of behaviors in a similar situation, unlike robots. This paper discusses human psychological phenomena during communication from the point of view of internal and external factors, such as perception, memory, and emotional information. Based on these, we introduce the personality affected robotic emotional model and the emotion affected associative memory model for the robot. We organize an interactive robot system to provide suitable decisions for the robot. Results from interactive communication experiments indicate that the robot is able to perform different actions based on internal and external factors