An affective decision-making model with applications to social robotics

Abstract

With the proliferation of information and communication technologies, especially with recent developments in Artificial Intelligence, social robots at home and the workplace are no longer being treated as lifeless and emotionless, leading to proposals which aim at incorporating affective elements within agents. Advances in areas such as affective decision-making and affective computing drive this interest. Our motivation in this paper is to use affection as a basic element within a decision-making process to facilitate robotic agents providing more seemingly human responses. We use earlier research in cognitive science and psychology to provide a model for an autonomous agent that makes decisions partly influenced by affective factors when interacting with humans and other agents. The factors included are emotions, mood, personality traits, and activation sets in relation with impulsive behavior. We describe several simulations with our model to study and compare its performance when facing various types of users. Through them, we essentially showcase that our model allows for a powerful agent design mechanism regulating its behavior and provides greater decision-making adaptivity when compared to emotionless agents and simpler emotional models. We conclude describing potential uses of our model in several application areas.