The Role of Forgetting in Learning
TL;DR — A 1988 machine-learning paper showing that most knowledge a program learned was harmful to it, and that random forgetting improved performance.
From the proceedings of the Fifth International Conference on Machine Learning (Ann Arbor, 1988). Seven pages.
The authors analyse “the economics of learning” and argue that knowledge can have negative value. In experiments with a program that learns to traverse state spaces, most of what it acquired was correct, came from similar problems, and still made it worse. The value of a piece of knowledge depended on what else was known, and random forgetting sometimes improved performance substantially.
What it is: a short conference paper with one experimental setup. The posted CiteSeerX link no longer serves the file; this copy is from Markovitch’s Technion page.
Where this came from
- r/obscurePDFs post, February 2019 — “The Role of Forgetting in Learning, by Shaul Markovitch and Paul D Scott (Fifth Int’l Conference on Machine Learning 1988)”. Routing record: The obscurePDFs Subreddit
- Link as posted: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.78.5851&rep=rep1&type=pdf
7 pages. A copy is archived locally against link rot; the header links the original source.