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A Two-Armed Bandit Collective for Hierarchical Examplar Based Mining of Frequent Itemsets with Applications to Intrusion Detection Read chapter Read first chapter

2014 | OriginalPaper | Chapter

Extended Learning Method for Designation of Co-operation

Authors : Edyta Kucharska, Ewa Dudek-Dyduch

Published in: Transactions on Computational Collective Intelligence XIV

Publisher: Springer Berlin Heidelberg

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Abstract

The aim of the paper is to present a new machine learning method for determining intelligent co-operation at project realization. The method uses local optimization task of a special form and is based on learning idea. Additionally, the information gathered during a searching process is used to prune non-perspective solutions. The paper presents a formal approach to creation of constructive algorithms that use a sophisticated local optimization and are based on a formal definition of multistage decision process. It also proposes a general conception of creation local optimization tasks for different problems as well as a conception of local optimization task modification on basis of acquired information. To illustrate the conceptions, the learning algorithm for NP-hard scheduling problem is presented as well as results of computer experiments.

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Metadata
Title
Extended Learning Method for Designation of Co-operation
Authors
Edyta Kucharska
Ewa Dudek-Dyduch
Copyright Year
2014
Publisher
Springer Berlin Heidelberg
Book
Transactions on Computational Collective Intelligence XIV

Print ISBN: 978-3-662-44508-2

Electronic ISBN: 978-3-662-44509-9

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-662-44509-9_7

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