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Can Binary Decision Diagrams predict concept complexity in human learning?

Shtrepi, Bekli (2021) Can Binary Decision Diagrams predict concept complexity in human learning? Bachelor's Thesis, Artificial Intelligence.

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Abstract

This project is about predicting the difficulty of concept learning in humans using Binary Decision Diagrams. The subjective difficulty of learning has been studied in the past using multiple other methods, including propositional logical formulas (Feldman, 2000). In this paper, we take a look at previous research data, and we use those results to see whether BDDs are able to make a correct prediction. We find a moderate correlation of 67% between the depth of the BDD and the Boolean complexity of the corresponding concepts. We also find a much stronger correlation of 86% between the number of nodes of the BDD and the Boolean complexity of the concept.

Item Type: Thesis (Bachelor's Thesis)
Supervisor name: Gattinger, B.R.M.
Degree programme: Artificial Intelligence
Thesis type: Bachelor's Thesis
Language: English
Date Deposited: 17 Feb 2021 11:16
Last Modified: 17 Feb 2021 11:16
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/23975

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