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Reinforcement Learning Based Artificial Immune Classifier
Author
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-08
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
One of the widely used methods for classification that is a decision-making process is artificial immune systems.
Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems.
In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach.
This approach uses reinforcement learning to find better antibody with immune operators.
The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability.
The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA.
Some benchmark data and remote image data are used for experimental results.
The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method.
American Psychological Association (APA)
Karakose, Mehmet. 2013. Reinforcement Learning Based Artificial Immune Classifier. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1012547
Modern Language Association (MLA)
Karakose, Mehmet. Reinforcement Learning Based Artificial Immune Classifier. The Scientific World Journal No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1012547
American Medical Association (AMA)
Karakose, Mehmet. Reinforcement Learning Based Artificial Immune Classifier. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1012547
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1012547