International Journal of Science, Engineering and TechnologyAuthors: Sandeep Dalal, Dr Jyoti Chaudhary
Abstract: We are witnessing transitioning from rule-based systems to complex deep neural architectures in the way Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) and Explainable AI (XAI) that have evolved over the past decades and keep on growing. This paper presents a comprehensive and detailed literature review in a timeline sequence while highlighting key models and the important methods that have been developed from year 1950 to year 2025. The study categorizes all the major developments done into AI, ML, DL and XAI providing a detailed comparative and logical analysis of their working principles and their limitations. Here in this proposed review paper it identifies the research gaps and the major emerging trends such as hybrid XAI systems along with human centered AI systems.
DOI: http://doi.org/10.5281/zenodo.21768659
