An analytical study on causal induction

Automatic causal discovery is a challenge research with extraordinary significance in sceintific research and in many real world problems where recovery of causes and effects and their causality relationship is an essential task. This paper firstly introduces the causality and perspectives of causal discovery. Then it provides an anlaysis on the three major approaches that are proposed in the last decades for the automatic discovery of casual models from given data. Afterwards it presents a analysis on the capability and applicability of the different proposed approaches followed by a conclusion on the potentials and the future research.