초록: Computer programs can complete many tasks much more effectively and efficiently than human beings, such as calculating the product of two large numbers, or finding all occurrences of a string in a long text. However, the performance of computers on many intelligent tasks is still low. For example, in a chatting scenario, computers often generate irrelevant or incorrect responses; we can easily find amusing results in automatic machine translations; and it is still a very challenging task for state-of-the-art computer programs to solve even primary-school-level math word problems. As an exploration project in grounded and executable semantic parsing and an effort to push toward real world knowledge computing, the SigmaDolphin project at MSRA aims to build an intelligent computer system that can automatically solve math word problems. In this talk, I will summarize our findings in addressing the three major challenges of math word problem solving: dataset creation, math word problem understanding and math equation generation.