Teaching randomized learners with feedback

Balbach, Frank J.; Zeugmann, Thomas

Information and Computation, 2011, 209(3), 296-319

Permalink : https://hdl.handle.net/2115/45035

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ファイル	フォーマット	サイズ	閲覧回数	説明
IC209-3_296-319	pdf	365 KB	765

アクセス権	open access
URI	https://hdl.handle.net/2115/45035
タイトル	Teaching randomized learners with feedback
著者	著者名 Balbach, Frank J.
著者	著者名 Zeugmann, Thomas
言語	英語
キーワード	Algorithmic teaching
	Randomized algorithms
	Computational complexity
発行日	2011-03
出版者	Elsevier
収録物名	Information and Computation
巻(号)	209(3)
ページ	296-319
抄録	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.
資源タイプ	学術雑誌論文
出版タイプ	Accepted Manuscript
PISSN	0890-5401
関連情報 (isVersionOf)	出版社版DOI https://doi.org/10.1016/j.ic.2010.11.005