Machine learning and symbolic reasoning have been two main approaches to build intelligent systems. Symbolic reasoning has been used in many applications by making use of expressive symbolic representations to encode prior knowledge, conduct complex reasoning and provide explanations. Recently, machine learning has enabled various successful applications by learning from...
Designing intelligent systems that can answer questions has been an ongoing and active challenge for the artificial intelligence community. In the past, researchers were focused on producing specialized language systems for particular domains and datasets. Such approaches would require deeper-than-ideal amounts of expertise to design, and often necessitated the expensive...