Consistent and coherent learning with δ-delay

Yohji Akama, Thomas Zeugmann

研究成果: Article査読

4 被引用数 (Scopus)

抄録

A consistent learner is required to correctly and completely reflect in its actual hypothesis all data received so far. Though this demand sounds quite plausible, it may lead to the unsolvability of the learning problem. Therefore, in the present paper several variations of consistent learning are introduced and studied. These variations allow a so-called δ-delay relaxing the consistency demand to all but the last δ data. Additionally, we introduce the notion of coherent learning (again with δ-delay) requiring the learner to correctly reflect only the last datum (only the n - δth datum) seen. Our results are manyfold. First, we provide characterizations for consistent learning with δ-delay in terms of complexity and computable numberings. Second, we establish strict hierarchies for all consistent learning models with δ-delay in dependence on δ. Finally, it is shown that all models of coherent learning with δ-delay are exactly as powerful as their corresponding consistent learning models with δ-delay.

本文言語English
ページ(範囲)1362-1374
ページ数13
ジャーナルInformation and Computation
206
11
DOI
出版ステータスPublished - 2008 11

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • 情報システム
  • コンピュータ サイエンスの応用
  • 計算理論と計算数学

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