Lifelong Machine Learning With Adaptive Resonance Theory

Author

Sasha Alexander Petrenko, Missouri University of Science and Technology

Keywords and Phrases

Adaptive resonance theory; Artificial intelligence; Catastrophic forgetting; Deep learning; Lifelong machine learning

Abstract

"This publication option dissertation is composed of three papers concerning the study of the problem lifelong machine learning with Adaptive Resonance Theory (ART) algorithms. Lifelong learning (L2) is a challenging machine learning paradigm that both encompasses and formalizes the fields of continual learning and incremental learning. The field is concerned with the mitigation of the phenomenon of catastrophic forgetting whereby learning agents that are faced with incrementally novel information deleteriously overwrite previous knowledge if that learning process is not regularized to counteract this consequence. ART algorithms solve this stability-plasticity dilemma by optimally assigning learning to categories or instantiating new knowledge when information is sufficiently novel. While the appeal of deep neural networks is their capacity to learning useful feature manifolds simultaneously with the task at hand, they are especially subject to catastrophic forgetting both by their hierarchical architectures and by the current techniques used to train them.

The publications of this dissertation explore techniques for adapting ART algorithms from novel application domains in computer vision and biomedical data analysis to formulations of deep learning networks that complement and combine the unique strengths of adaptive resonance and deep learning to tackle the lifelong machine learning problem"-- Abstract, p. iv

Advisor(s)

Wunsch, Donald C.

Committee Member(s)

Beetner, Daryl G.
Pernicka, Henry J.
Stanley, R. Joe
Kimball, Jonathan W.

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Computer Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2025

Pagination

xiii, 165 pages

Note about bibliography

Includes_bibliographical_references_(pages 56, 97, 138 and 161-163)

Rights

©2024 Sasha Alexander Petrenko , All Rights Reserved

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12469

Recommended Citation

Petrenko, Sasha Alexander, "Lifelong Machine Learning With Adaptive Resonance Theory" (2025). Doctoral Dissertations. 3373.
https://scholarsmine.mst.edu/doctoral_dissertations/3373