التفاصيل البيبلوغرافية
| العنوان: |
Lateralized Learning to Solve Complex Boolean Problems. |
| المؤلفون: |
Siddique A, Browne WN, Grimshaw GM |
| المصدر: |
IEEE transactions on cybernetics [IEEE Trans Cybern] 2023 Nov; Vol. 53 (11), pp. 6761-6775. Date of Electronic Publication: 2023 Oct 17. |
| نوع المنشور: |
Journal Article |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: Institute of Electrical and Electronics Engineers Country of Publication: United States NLM ID: 101609393 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2168-2275 (Electronic) Linking ISSN: 21682267 NLM ISO Abbreviation: IEEE Trans Cybern Subsets: MEDLINE |
| أسماء مطبوعة: |
Original Publication: New York, NY : Institute of Electrical and Electronics Engineers, 2013- |
| مواضيع طبية MeSH: |
Brain* , Machine Learning* |
| مستخلص: |
Modern classifier systems can effectively classify targets that consist of simple patterns. However, they can fail to detect hierarchical patterns of features that exist in many real-world problems, such as understanding speech or recognizing object ontologies. Biological nervous systems have the ability to abstract knowledge from simple and small-scale problems in order to then apply it to resolve more complex problems in similar and related domains. It is thought that lateral asymmetry of biological brains allows modular learning to occur at different levels of abstraction, which can then be transferred between tasks. This work develops a novel evolutionary machine-learning (EML) system that incorporates lateralization and modular learning at different levels of abstraction. The results of analyzable Boolean tasks show that the lateralized system has the ability to encapsulate underlying knowledge patterns in the form of building blocks of knowledge (BBK). Lateralized abstraction transforms complex problems into simple ones by reusing general patterns (e.g., any parity problem becomes a sequence of the 2-bit parity problem). By enabling abstraction in evolutionary computation, the lateralized system is able to identify complex patterns (e.g., in hierarchical multiplexer (HMux) problems) better than existing systems. |
| تواريخ الأحداث: |
Date Created: 20220427 Date Completed: 20231023 Latest Revision: 20231023 |
| رمز التحديث: |
20240628 |
| DOI: |
10.1109/TCYB.2022.3166119 |
| PMID: |
35476559 |
| قاعدة البيانات: |
MEDLINE |
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