Learning Probabilistic Logic Models with Human Advice

摘要

We consider the problem of interactive machine learning for rich, structured and noisy domains. We present a recently successful learning algorithm and provide several extensions for incorporating rich, high level, human feedback. We then discuss some open problems in this area.