A relatively new scientific field that aims to study the developmental mechanisms and architectures for lifelong learning in machines. Typically it involves formalizing, validating and extending models from neuroscience, developmental psychology, and evolutionary biology, specifically by attempting to implement the models in robots. Results are expected to feedback into existing theories, or produce novel theories about human and animal development.
Published in Chapter:
Developing Robot Emotions through Interaction with Caregivers
Angelica Lim (Kyoto University, Japan) and Hiroshi G. Okuno (Kyoto University, Japan & Waseda University, Japan)
Copyright: © 2015
|Pages: 22
DOI: 10.4018/978-1-4666-7278-9.ch015
Abstract
In this chapter, the authors explore social constructivist theories of emotion, which suggest that emotional behaviors are developed through experience, rather than innate. The authors' approach to artificial emotions follows this paradigm, stemming from a relatively young field called developmental or ‘epigenetic' robotics. The chapter describes the design and implementation of a robot called MEI (multimodal emotional intelligence) with an emotion development system. MEI synchronizes to humans through voice and movement dynamics, based on mirror mechanism-like entrainment. Via typical caregiver interactions, MEI associates these dynamics with its physical feeling, e.g. distress (low battery or excessive motor heat) or flourishing (homeostasis). Our experimental results show that emotion clusters developed through robot-directed motherese (“baby talk”) are similar to adult happiness and sadness, giving evidence to constructivist theories.