article

Multistrategy Theory Revision: Induction and Abductionin INTHELEX

Authors:

Floriana Esposito,

Giovanni Semeraro,

Nicola Fanizzi,

Stefano FerilliAuthors Info & Claims

Machine Learning, Volume 38, Issue 1-2

Pages 133 - 156

https://doi.org/10.1023/A:1007638124237

Published: 01 January 2000 Publication History

Abstract

This paper presents an integration of induction and abduction in INTHELEX, a prototypical incremental learning system. The refinement operators perform theory revision in a search space whose structure is induced by a quasi-ordering, derived from Plotkin's &thetas;-subsumption, compliant with the principle of Object Identity. A reduced complexity of the refinement is obtained, without a major loss in terms of expressiveness. These inductive operators have been proven ideal for this search space. Abduction supports the inductive operators in the completion of the incoming new observations. Experiments have been run on a standard dataset about family trees as well as in the domain of document classification to prove the effectiveness of such multistrategy incremental learning system with respect to a classical batch algorithm.

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Cited By

Huang YDai WJiang YZhou ZWilliams BChen YNeville J(2023)Enabling knowledge refinement upon new concepts in abductive learningProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i7.25959(7928-7935)Online publication date: 7-Feb-2023
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de Carolis BFerilli SMacchiarulo NBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Ambient Assisted Living and Social Robots: Towards Learning Relations between User’s Daily Routines and MoodAdjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3511047.3537691(123-129)Online publication date: 4-Jul-2022
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Index Terms

Multistrategy Theory Revision: Induction and Abductionin INTHELEX
1. Computing methodologies
2. Mathematics of computing
  1. Discrete mathematics

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Information & Contributors

Information

Published In

cover image Machine Language

Machine Language Volume 38, Issue 1-2

Special issue on multistrategy learning

Jan./Feb. 2000

227 pages

ISSN:0885-6125

Editors:
Robert C. Holte
Univ. of Ottawa, Ottawa, Ont., Canada
,
Lorenza Saitta
Univ. del Piemonte Oriental Alessandria, Italy
,
Floriana Esposito
Univ. di Bari, Bari, Italy
,
Ryszard Michalski
George Mason Univ., Fairfax, VA

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Copyright © Copyright © 2000 Kluwer Academic Publishers.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 January 2000

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Huang YDai WJiang YZhou ZWilliams BChen YNeville J(2023)Enabling knowledge refinement upon new concepts in abductive learningProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i7.25959(7928-7935)Online publication date: 7-Feb-2023
https://dl.acm.org/doi/10.1609/aaai.v37i7.25959
de Carolis BFerilli SMacchiarulo NBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Ambient Assisted Living and Social Robots: Towards Learning Relations between User’s Daily Routines and MoodAdjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3511047.3537691(123-129)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3511047.3537691
Angelastro SDe Carolis BFerilli S(2019)Learning and Predicting User Pairwise Preferences from Emotions and Gaze BehaviorIEEE/WIC/ACM International Conference on Web Intelligence - Companion Volume10.1145/3358695.3361747(72-79)Online publication date: 14-Oct-2019
https://dl.acm.org/doi/10.1145/3358695.3361747
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Paes AZaverucha GCosta V(2017)On the use of stochastic local search techniques to revise first-order logic theories from examplesMachine Language10.1007/s10994-016-5595-3106:2(197-241)Online publication date: 1-Feb-2017
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Ferilli S(2016)Predicate invention-based specialization in Inductive Logic ProgrammingJournal of Intelligent Information Systems10.1007/s10844-016-0412-947:1(33-55)Online publication date: 1-Aug-2016
https://dl.acm.org/doi/10.1007/s10844-016-0412-9
Ferilli SRedavid DEsposito F(2015)Logic-based incremental process miningProceedings of the 2015th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part III10.5555/3120539.3120558(218-221)Online publication date: 7-Sep-2015
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Carolis BFerilli SRedavid D(2015)Incremental Learning of Daily Routines as Workflows in a Smart Home EnvironmentACM Transactions on Interactive Intelligent Systems10.1145/26750634:4(1-23)Online publication date: 28-Jan-2015
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Ferilli SEsposito F(2013)A Logic Framework for Incremental Learning of Process ModelsFundamenta Informaticae10.5555/2595015.2595017128:4(413-443)Online publication date: 1-Oct-2013
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