CMU Artificial Intelligence Repository
RWM: Refinement With Macros
RWM (Refinement With Macros) is an interactive system for learning
problem solving strategies. RWM incorporates two techniques, namely
Refinement and Macro Generation. The input to the RWM is the definition
of a problem, the output is a strategy for solving the given problem.
A strategy is a sequence of subproblems which are easier then the original
problem, and when solved in the the given order it yields a solution
for the original problem.
FTP repositories for machine learning include
Requires: Common Lisp
Ports: Tested under Lucid CL.
CD-ROM: Prime Time Freeware for AI, Issue 1-1
Author(s): H. Altay Guvenir
Machine Learning!Macro Generation,
Machine Learning!Refinement, RWM
H. A. Guvenir and G. W. Ernst, "Learning Problem Solving Strategies
Using Refinement and Macro Generation", Artificial Intelligence, Vol.
44, No. 1-2, July, 1990. pp. 209-243.
H. A. Guvenir and V. Akman, "Problem Representation for Refinement",
Mind and Machines, Vol. 2, No. 3, August 1992. pp 267-282.
H. A. Guvenir and G. W. Ernst, "A Method for Learning Problem Solving
Strategies", Proceedings of the AAAI Spring Symposium Series, Stanford
University, March 1988. pp 31-35.
Last Web update on Mon Feb 13 10:24:34 1995