Using Emotions for Behaviour-Selection Learning

Emotions play a very important role in human behaviour and social interaction. In this paper we present a control architecture which uses emotions in the behaviour selection process of autonomous and social agents. The state of the agent is determined by its internal state, defined by its dominant motivation, and its relation with the external objects including other agents. The behaviour selection is learned by the agent using standard and multiagent Qlearning algorithms. The considered emotions are fear, happiness and sadness. The role of these emotions in this architecture is different, while the learning algorithms use happiness/sadness of the agent as positive/negative reinforcement signals, the emotion fear is used to prevent the agent of choosing dangerous actions as well as a motivation.

• Type: Conference
• Year: 2006
• Where: ECAI
• Authors: Maria Malfaz, Miguel Angel Salichs
• Keywords: Artificial Intelligence, Behaviour Selection, Behaviour Selection Process, ECAI 2006, Multiagent Qlearning Algorithms