Learning Operator Semantics by Analogy

Book One

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 3

Cognitive Modeling

This paper proposes a cognitive model for human procedural skill acquisition based on problem solving in problem spaces and the use of analogy for building the representation of operator semantics. Protocol data of computer-naive subjects learning the EMACS text editor suggests that they use their knowledge of typewriting to decide which commands to use in performing editing tasks. We propose a formal method of analysis that compares operators in two problem spaces (based on posrcondirion similarity) and generates misconceptions (based on pre- and postcondition differences). Comparing these predicted misconceptions with error data and verbal comments in problem solving episodes validates this analysis.