Unsupervised Symbol Grounding and Cognitive Bootstrapping in Cognitive Vision

摘要

In conventional computer vision systems symbol grounding is invariably established via supervised learning. We investigate unsu-pervised symbol grounding mechanisms that rely on perception action coupling. The mechanisms involve unsupervised clustering of observed actions and percepts. Their association gives rise to behaviours that emulate human action. The capability of the system is demonstrated on the problem of mimicking shape puzzle solving. It is argued that the same mechanisms support unsupervised cognitive bootstrapping in cognitive vision.