Using Matchboxes to Teach the Basics of Machine Learning: an Analysis of (Possible) Misconceptions

Erik Marx, Thiemo Leonhardt, David Baberowski, Nadine Bergner
Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:25-29, 2022.

Abstract

The idea of chess-playing matchboxes, conceived by Martin Gardner as early as 1962, is becoming more and more relevant in learning materials in the area of AI and Machine Learning. Thus, it can be found in a large number of workshops and papers as an innovative teaching method to convey the basic ideas of reinforcement learning. In this paper the concept and its variations will be presented and the advantages of this analog approach will be shown. At the same time, however, the limitations of the approach are analyzed and the question of alternatives is raised.

Cite this Paper

BibTeX
@InProceedings{pmlr-v170-marx22a, title = {Using Matchboxes to Teach the Basics of Machine Learning: an Analysis of (Possible) Misconceptions}, author = {Marx, Erik and Leonhardt, Thiemo and Baberowski, David and Bergner, Nadine}, booktitle = {Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop}, pages = {25--29}, year = {2022}, editor = {Kinnaird, Katherine M. and Steinbach, Peter and Guhr, Oliver}, volume = {170}, series = {Proceedings of Machine Learning Research}, month = {08--13 Sep}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v170/marx22a/marx22a.pdf}, url = {https://proceedings.mlr.press/v170/marx22a.html}, abstract = {The idea of chess-playing matchboxes, conceived by Martin Gardner as early as 1962, is becoming more and more relevant in learning materials in the area of AI and Machine Learning. Thus, it can be found in a large number of workshops and papers as an innovative teaching method to convey the basic ideas of reinforcement learning. In this paper the concept and its variations will be presented and the advantages of this analog approach will be shown. At the same time, however, the limitations of the approach are analyzed and the question of alternatives is raised.} }
Endnote
%0 Conference Paper %T Using Matchboxes to Teach the Basics of Machine Learning: an Analysis of (Possible) Misconceptions %A Erik Marx %A Thiemo Leonhardt %A David Baberowski %A Nadine Bergner %B Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop %C Proceedings of Machine Learning Research %D 2022 %E Katherine M. Kinnaird %E Peter Steinbach %E Oliver Guhr %F pmlr-v170-marx22a %I PMLR %P 25--29 %U https://proceedings.mlr.press/v170/marx22a.html %V 170 %X The idea of chess-playing matchboxes, conceived by Martin Gardner as early as 1962, is becoming more and more relevant in learning materials in the area of AI and Machine Learning. Thus, it can be found in a large number of workshops and papers as an innovative teaching method to convey the basic ideas of reinforcement learning. In this paper the concept and its variations will be presented and the advantages of this analog approach will be shown. At the same time, however, the limitations of the approach are analyzed and the question of alternatives is raised.
APA
Marx, E., Leonhardt, T., Baberowski, D. & Bergner, N.. (2022). Using Matchboxes to Teach the Basics of Machine Learning: an Analysis of (Possible) Misconceptions. Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, in Proceedings of Machine Learning Research 170:25-29 Available from https://proceedings.mlr.press/v170/marx22a.html.

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