A Bayesian Robot That Distinguishes "Self" from "Other"

摘要

A Bayesian kinesthetic-visual matching model allows a humanoid robot to perform mirror self-recognition without social understanding.The robot learns the relationship between its own motor activity and perceived motion by observing the movements of its arm for four minutes.Over this time, it builds a simple dynamic Bayesian model that relates these two events, and uses this self model to build a model of "animate others" that is a copy of its self model but with the motor state hidden.Presented with a mirror, the robot then judges its mirror image to match its "self" model, while people are judged to be "animate others."