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Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Information Science and Technology / Faculty of Information Science and Technology >
Peer-reviewed Journal Articles, etc >
Teaching randomized learners with feedback
| Title: | Teaching randomized learners with feedback |
| Authors: | Balbach, Frank J. Browse this author | | Zeugmann, Thomas Browse this author |
| Keywords: | Algorithmic teaching | | Randomized algorithms | | Computational complexity |
| Issue Date: | Mar-2011 |
| Publisher: | Elsevier |
| Journal Title: | Information and Computation |
| Volume: | 209 |
| Issue: | 3 |
| Start Page: | 296 |
| End Page: | 319 |
| Publisher DOI: | 10.1016/j.ic.2010.11.005 |
| Abstract: | The present paper introduces a new model for teaching randomized learners. Our new model, though based on the classical teaching dimension model, allows to study the influence of the learner's memory size and of the presence or absence of feedback. Moreover, in the new model the order in which examples are presented may influence the teaching process. The resulting models are related to Markov decision processes, and characterizations of optimal teachers for memoryless learners with feedback and for learners with infinite memory and feedback are shown. Furthermore, in the new model it is possible to investigate new aspects of teaching like teaching from positive data only or teaching with inconsistent teachers. Characterization theorems for teachability from positive data for both ordinary teachers and inconsistent teachers with and without feedback are provided. |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/45035 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: Zeugmann Thomas
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