Bias, Version Spaces and Valiant's Learning Framework

We present an overview of some recent theoretical results in the learning framework introduced by Valiant in (Valiant, 1984) and further developed in (Valiant 1985; Blumer, et. al., 1986, in press; Pitt & Valiant, 1986; Haussler, 1986; Angluin & Laird, 1986; Angluin, 1986; Rivest, 1986; Haussler, 1987; Kearns, et. al., 1987). Our focus is on applications to AI problems of learning from examples as given in (Haussler, 1986, 1987) and (Kearns, et. al., 1987), along with a comparison to the work of Mitchell on version spaces (Mitchell, 1982). We discuss learning problems for both attribute-based and structural domains.