a computational model of teaching
Goldman and Kearns [GK91] recently introduced a notion of the teaching dimension of a concept class. The teaching dimension is intended to capture the combinatorial difficulty of teaching a concept class. We present a computational analog which allows us to make statements about bounded-complexity teachers and learners, and we extend the model by incorporating trusted information . Under this extended model, we modify algorithms for learning several expressive classes in the exact identification model of Angluin [Ang88]. We study the relationships between variants of these models, and also touch on a relationship with distribution-free learning.
computer modeling computation model teaching concept class analog learning algorithm express identification relationships touch complexity distributed