Algorithmic Learning for Knowledge-Based Systems

GOSLER Final Report

AvKlaus P. Jantke,Steffen Lange

Häftad, Engelska, 1995

Del i serien Lecture Notes in Computer Science

581 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

This book is the final report on a comprehensive basic research project, named GOSLER on algorithmic learning for knowledge-based systems supported by the German Federal Ministry of Research and Technology during the years 1991 - 1994. This research effort was focused on the study of fundamental learnability problems integrating theoretical research with the development of tools and experimental investigation.The contributions by 11 participants in the GOSLER project is complemented by contributions from 23 researchers from abroad. Thus the volume provides a competent introduction to algorithmic learning theory.

Produktinformation

Utgivningsdatum:1995-08-09
Mått:155 x 235 x 29 mm
Vikt:797 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:522
Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN:9783540602170

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Innehållsförteckning

Learning and consistency.- Error detecting in inductive inference.- Learning from good examples.- Towards reduction arguments for FINite learning.- Not-so-nearly-minimal-size program inference (preliminary report).- Optimization problem in inductive inference.- On identification by teams and probabilistic machines.- Topological considerations in composing teams of learning machines.- Probabilistic versus deterministic memory limited learning.- Classification using information.- Classifying recursive predicates and languages.- A guided tour across the boundaries of learning recursive languages.- Pattern inference.- Inductive learning of recurrence-term languages from positive data.- Learning formal languages based on control sets.- Learning in case-based classification algorithms.- Optimal strategies — Learning from examples — Boolean equations.- Feature construction during tree learning.- On lower bounds for the depth of threshold circuits with weights from {?1,0,+1}.- Structuring neural networks and PAC-Learning.- Inductive synthesis of rewrite programs.- TLPS — A term rewriting laboratory (not only) for experiments in automatic program synthesis.- GoslerP — A logic programming tool for inductive inference.