MUKHOP%RCSJJ%gmr.com@RELAY.CS.NET (11/19/86)
I read with interest the abstract for Richard M. Keller's talk, "The Role of Explicit Contextual Knowledge in Learning Concepts to Improve Performance" (V4 #258), part of which is reproduced below: > This dissertation addresses some of the difficulties encountered > when using artificial intelligence-based, inductive concept learning > methods to improve an existing system's performance. The underlying > problem is that inductive methods are insensitive to changes in the > system being improved by learning. This insensitivity is due to the > manner in which contextual knowledge is represented in an inductive > system. Contextual knowledge consists of knowledge about the context > in which concept learning takes place, including knowledge about the > desired form and content of concept descriptions to be learned (target > concept knowledge), and knowledge about the system to be improved by > learning and the type of improvement desired (performance system > knowledge). > ... > To investigate the thesis, this study introduces an alternative > concept learning framework -- the concept operationalization framework > -- that requires various types of contextual knowledge as explicit > inputs. >... Isn't this described in the literature as a two-layer learning system (multi-layer in the general case) of which Samuel's checkers player is one of the earliest examples? What are the differences, if any? Uttam Mukhopadhyay GM Research Labs