Special Issue on

Algorithmic Learning Theory

for ALT '95 in

ALT 95 Logo

Theoretical Computer Science Vol. 185, No. 1, October 10, 1997.

The Special Issue on Algorithmic Learning Theory for ALT '95 in Theoretical Computer Science has been edited by T. Zeugmann.

Table of Contents

Thomas Zeugmann.

pp. 1

John Kececioglu, Ming Li, and John Tromp.
Inferring a DNA sequence from erroneous copies,

pp. 3 - 13

Yasubumi Sakakibara.
Recent advances of grammatical inference,

pp. 15 - 45

Hiroki Arimura, Hiroki Ishizaka, and Takeshi Shinohara.
Learning unions of tree patterns using queries,

pp. 47 - 62

Takeshi Koshiba, Erkki Mäkinen, and Yuji Takada.
Learning deterministic even linear languages from positive examples,

pp. 63 - 79

Léa Meyer.
Probabilistic language learning under monotonicity constraints,

pp. 81 - 128

Frank Stephan.
Noisy inference and oracles,

pp. 129 - 157

Peter Auer.
Learning nested differences in the presence of malicious noise,

pp. 159 - 175

Eiji Takimoto, Akira Miyashiro, Akira Maruoka, and Yoshifumi Sakai.
Learning orthogonal F-Horn formulas,

pp. 177 - 190

M. R. K. Krishna Rao.
A framework for incremental learning of logic programs,

pp. 193 - 213

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