Symbol Emergence in Robotics for Long-Term Human-Robot Collaboration

Abstract

Humans can acquire language through physical interaction with their environment and semiotic interaction with other people. It is very important to understand how humans can form a symbol system and obtain semiotic skills through their autonomous mental development from a computational point of view. A machine learning system that enables a robot to obtain and modulate its symbol system is crucially important to develop robotic systems that achieve long-term human-robot communication and collaboration. In this paper, I introduce the basis of our research field and related topics. Specifically, I describe the concept of symbol emergence systems and the recent research topics , e.g., multimodal categorization, spatial concept formation, language acquisition, and double articulation analysis, that will contribute to future human-robot communication and collaboration.