Combining Weak Learning Heuristics in General Problem Solvers
Abstract
This paper is concerned with state space problem \nsolvers that achieve generality by learning strong \nheuristics through experience in a particular domain. We specifically consider two ways of learning by analysing past solutions that can improve future problem solving: creating macros and the chunks. A method of learning search heuristics is specified which is related to 'chunking' but which complements the use \nof macros within a goal directed system. An example of the creation and combined use of macros and chunks, taken from an implemented system, is described.
Cite
Text
McCluskey. "Combining Weak Learning Heuristics in General Problem Solvers." International Joint Conference on Artificial Intelligence, 1987.Markdown
[McCluskey. "Combining Weak Learning Heuristics in General Problem Solvers." International Joint Conference on Artificial Intelligence, 1987.](https://mlanthology.org/ijcai/1987/mccluskey1987ijcai-combining/)BibTeX
@inproceedings{mccluskey1987ijcai-combining,
title = {{Combining Weak Learning Heuristics in General Problem Solvers}},
author = {McCluskey, Thomas Leo},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1987},
pages = {331-333},
url = {https://mlanthology.org/ijcai/1987/mccluskey1987ijcai-combining/}
}