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Meta-Learning in Computational Intelligence pp 157–177Cite as

Computational Intelligence for Meta-Learning: A Promising Avenue of Research

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 358))

Abstract

The common practices of machine learning appear to be frustrated by a number of theoretical results denying the possibility of any meaningful implementation of a “superior” learning algorithm. However, there exist some general assumptions that, even when overlooked, preside the activity of researchers and practitioners. A thorough reflection over such essential premises brings forward the meta-learning approach as the most suitable for escaping the long-dated riddle of induction claiming also an epistemologic soundness. Several examples of meta-learning models can be found in literature, yet the combination of computational intelligence techniques with meta-learning models still remains scarcely explored. Our contribution to this particular research line consists in the realisation of Mindful, a meta-learning system based on the neuro-fuzzy hybridisation. We present the Mindful system firstly situating it inside the general context of the meta-learning frameworks proposed in literature. Finally, a complete session of experiments is illustrated, comprising both base-level and meta-level learning activity. The appreciable experimental results underline the suitability of the Mindful system for managing past accumulated learning experience while facing novel tasks.

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Authors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Bari, via E. Orabona, 4, 70125, Bari, Italy

    Ciro Castiello & Anna Maria Fanelli

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  1. Ciro Castiello
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  2. Anna Maria Fanelli
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  1. Department of Informatics, Nicolaus Copernicus University, ul. Grudzia̧dzka 5, 87-100, Toruń, Poland

    Norbert Jankowski , Włodzisław Duch  & Krzysztof Gra̧bczewski ,  & 

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Castiello, C., Fanelli, A.M. (2011). Computational Intelligence for Meta-Learning: A Promising Avenue of Research. In: Jankowski, N., Duch, W., Gra̧bczewski, K. (eds) Meta-Learning in Computational Intelligence. Studies in Computational Intelligence, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20980-2_5

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  • DOI: https://doi.org/10.1007/978-3-642-20980-2_5

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