article

Interactive Concept-Learning and Constructive Induction by Analogy

Authors:

Luc De Raedt,

Maurice BruynoogheAuthors Info & Claims

Machine Learning, Volume 8, Issue 2

Pages 107 - 150

https://doi.org/10.1023/A:1022664419589

Published: 01 March 1992 Publication History

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Abstract

The available concept-learners only partially fulfill the needs imposed by the learning apprentice generation of learners. We present a novel approach to interactive concept-learning and constructive induction that better fits the requirements imposed by the learning apprentice paradigm. The approach is incorporated in the system Clint-Cia, which integrates several user-friendly features into one working whole: it is interactive, generates examples, shifts its bias, identifies concepts in the limit, copes with indirect relevance, recovers from errors, performs constructive induction and invents new concepts by analogy to previously learned ones.

Cited By

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Pereira LPinto A(2009)Adaptive reasoning for cooperative agentsProceedings of the 18th international conference on Applications of declarative programming and knowledge management10.5555/2008383.2008392(102-116)Online publication date: 3-Nov-2009
https://dl.acm.org/doi/10.5555/2008383.2008392
Davis JDomingos PDanyluk ABottou LLittman M(2009)Deep transfer via second-order Markov logicProceedings of the 26th Annual International Conference on Machine Learning10.1145/1553374.1553402(217-224)Online publication date: 14-Jun-2009
https://dl.acm.org/doi/10.1145/1553374.1553402
Koriche F(2004)Bias windowing for relational learningProceedings of the 16th European Conference on Artificial Intelligence10.5555/3000001.3000105(495-499)Online publication date: 22-Aug-2004
https://dl.acm.org/doi/10.5555/3000001.3000105
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Index Terms

Interactive Concept-Learning and Constructive Induction by Analogy
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Logic programming and answer set programming
  2. Machine learning
    1. Learning paradigms
    2. Machine learning approaches
      1. Instance-based learning
2. Theory of computation
  1. Logic
    1. Constraint and logic programming

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Information

Published In

Machine Language Volume 8, Issue 2

March 1992

114 pages

ISSN:0885-6125

Editors:
Jaime G. Carbonell
Carnegie-Mellon Univ., Pittsburgh, PA
,
Thomas Dietterich
Oregon State Univ., Corvallis, OR

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Kluwer Academic Publishers

United States

Publication History

Published: 01 March 1992

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Pereira LPinto A(2009)Adaptive reasoning for cooperative agentsProceedings of the 18th international conference on Applications of declarative programming and knowledge management10.5555/2008383.2008392(102-116)Online publication date: 3-Nov-2009
https://dl.acm.org/doi/10.5555/2008383.2008392
Davis JDomingos PDanyluk ABottou LLittman M(2009)Deep transfer via second-order Markov logicProceedings of the 26th Annual International Conference on Machine Learning10.1145/1553374.1553402(217-224)Online publication date: 14-Jun-2009
https://dl.acm.org/doi/10.1145/1553374.1553402
Koriche F(2004)Bias windowing for relational learningProceedings of the 16th European Conference on Artificial Intelligence10.5555/3000001.3000105(495-499)Online publication date: 22-Aug-2004
https://dl.acm.org/doi/10.5555/3000001.3000105
Lamma ERiguzzi FPereira L(2000)Strategies in Combined Learning via Logic ProgramsMachine Language10.1023/A:100768190649038:1-2(63-87)Online publication date: 1-Jan-2000
https://dl.acm.org/doi/10.1023/A%3A1007681906490
Srinivasan A(1999)A Study of Two Sampling Methods for Analyzing Large Datasets with ILPData Mining and Knowledge Discovery10.1023/A:10098241234623:1(95-123)Online publication date: 1-Mar-1999
https://dl.acm.org/doi/10.1023/A%3A1009824123462
Srinivasan AKing R(1999)Feature construction with Inductive Logic ProgrammingData Mining and Knowledge Discovery10.1023/A:10098158216453:1(37-57)Online publication date: 1-Mar-1999
https://dl.acm.org/doi/10.1023/A%3A1009815821645
Muggleton S(1994)Inductive logic programmingACM SIGART Bulletin10.1145/181668.1816715:1(5-11)Online publication date: 1-Jan-1994
https://dl.acm.org/doi/10.1145/181668.181671
Džeroski SMuggleton SRussell SHaussler D(1992)PAC-learnability of determinate logic programsProceedings of the fifth annual workshop on Computational learning theory10.1145/130385.130399(128-135)Online publication date: 1-Jul-1992
https://dl.acm.org/doi/10.1145/130385.130399

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Relational Reinforcement Learning

An Incremental Deductive Strategy for Controlling Constructive Induction in Learning from Examples

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