Motivation and competitive learning in a social robot

Abstract

This paper describes the motivation and learning subsystems of Arisco which is a mechatronic head with interactive capacity which includes high expressivity through gesturing, voice recognition, text to speech generation, visual tracking, and Internet information retrieval. The general architecture is first described in the paper. Then, the learning capacity of Arisco is addressed. It learns and performs associations between different stimulus responses through several dynamic neural networks, guided by motivational drives. A number of experiments are discussed, covering stimulus competition, habituation, classical and operant conditioning.