Paul Groth, Yolanda Gil
Humans often teach procedures through tutorial instruction to other humans. For computers, learning from natural human instruction remains a challenge as it is plagued with incompleteness and ambiguity. Instructions are often given out of order and are not always consistent. Moreover, humans assume that the learner has a wealth of knowledge and skills, which computers do not always have. Our goal is to develop an electronic student that can be made increasingly capable through research to learn from human tutorial instruction. Initially, we will provide our student with humanunderstandable instruction that is extended with many scaffolding statements that supplement the limited initial capabilities of the student. Over time, improvements to the system are driven and quantified by the removal of scaffolding instructions that are not considered to be natural for users to provide humans. This paper describes our initial design and implementation of this system, how it learns from scaffolded instruction in two different domains, and the initial relaxations of scaffolding that the system supports.