## Algorithmic Learning Theory: 4th International Workshop on Analogical and Inductive Inference, AII '94, 5th International Workshop on Algorithmic Learning Theory, ALT '94, Reinhardsbrunn Castle, Germany, October 10 - 15, 1994. ProceedingsThis volume presents the proceedings of the Fourth International Workshop on Analogical and Inductive Inference (AII '94) and the Fifth International Workshop on Algorithmic Learning Theory (ALT '94), held jointly at Reinhardsbrunn Castle, Germany in October 1994. (In future the AII and ALT workshops will be amalgamated and held under the single title of Algorithmic Learning Theory.) The book contains revised versions of 45 papers on all current aspects of computational learning theory; in particular, algorithmic learning, machine learning, analogical inference, inductive logic, case-based reasoning, and formal language learning are addressed. |

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### Contents

I | 1 |

II | 2 |

III | 6 |

IV | 8 |

V | 10 |

VI | 26 |

VII | 40 |

VIII | 56 |

XXV | 272 |

XXVI | 282 |

XXVII | 290 |

XXVIII | 301 |

XXIX | 317 |

XXX | 333 |

XXXI | 349 |

XXXII | 365 |

### Other editions - View all

Algorithmic Learning Theory: 4th International Workshop on Analogical and ... Setsuo Arikawa,Klaus P. Jantke No preview available - 1994 |

### Common terms and phrases

Abstract Algorithmic Learning Theory Angluin Artificial Intelligence assume clause Computational Learning Theory Computer Science concept class consider consistent constraints construct contains converges counterexamples defined Definition denote efficient exists finite set formula fuzzy analogy given goal Godel numbering grammar graph Hence hypothesis space identify indexed family inductive inference inferable from positive infinite information sequence initial segment input integer language learning learnable learning algorithm learning model least Lemma limit from positive logic programming Machine Learning Mi-gaining algorithm mind changes minimal concept minimally inferable mono-PCF monotonic natural numbers obtained oracle output PAC learnability pattern languages polynomial population learner positive data predicate mapping probability problem procedure Proof prove queries recursive languages refutably regular expression regular languages respect sample satisfies similarity measure strategy string subset synthesis target concept term Theorem total recursive functions tree pattern variable Zeugmann