International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Adaptive Learning Algorithms: Enabling Intelligent Software that Evolves with Data

Author(s) Sai Krishna Chirumamilla
Country United States
Abstract Adaptive learning algorithms are broadly considered a step forward in artificial intelligence innovation or development and are claimed to improve software processes with changeable data to make intelligent decisions and adapt readily. The broad availability of information has thus led to the emergence of numerous complexities in initial training models that were originally designed to be static and not as adaptive to alterations in the character and composition of data distribution and other user needs and expectations. Adaptive learning algorithms – This paper looks at mechanisms of adaptive learning algorithms, exploring, in detail, their architecture, elements and technologies that foster adaptability. The paper emphasizes reinforcement learning, online learning, and transfer learning methods. It discusses their implementation possibilities in different areas, including machine learning-based individualized learning approaches, healthcare, finance, and self-driving systems. A literature survey is also part of this paper, which provides a view of the literature on advancing adaptive learning and its key contributions. In addition to the methodology and results section, the empirical investigation outlines practical implications and potential future directions for implementing adaptive learning to support software intelligently.
Field Engineering
Published In Volume 2, Issue 4, July-August 2020
Published On 2020-08-06
DOI https://doi.org/10.36948/ijfmr.2020.v02i04.42913
Short DOI https://doi.org/g9gdnv
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E-ISSN 2582-2160
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