Evolution of artificial intelligence languages, a systematic literature review
Emmanuel Adetiba, Temitope John, Adekunle Akinrinmade, Funmilayo, Moninuola, Oladipupo Akintade, Joke Badejo

TL;DR
This systematic review analyzes the evolution of AI programming languages by examining 69 key studies, providing insights into their development, capabilities, limitations, and applications to guide future AI research and implementation.
Contribution
The paper offers a comprehensive overview of AI programming languages evolution, highlighting key languages and their roles in AI development.
Findings
LISP and PROLOG are the most discussed AI languages.
The review covers languages like Python, C++, ADA, and JAVA.
Insights into language capabilities and limitations are provided.
Abstract
The field of Artificial Intelligence (AI) has undoubtedly received significant attention in recent years. AI is being adopted to provide solutions to problems in fields such as medicine, engineering, education, government and several other domains. In order to analyze the state of the art of research in the field of AI, we present a systematic literature review focusing on the Evolution of AI programming languages. We followed the systematic literature review method by searching relevant databases like SCOPUS, IEEE Xplore and Google Scholar. EndNote reference manager was used to catalog the relevant extracted papers. Our search returned a total of 6565 documents, whereof 69 studies were retained. Of the 69 retained studies, 15 documents discussed LISP programming language, another 34 discussed PROLOG programming language, the remaining 20 documents were spread between Logic and Object…
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Taxonomy
TopicsAI-based Problem Solving and Planning · Computability, Logic, AI Algorithms · Machine Learning and Data Classification
MethodsAdaptive Discriminator Augmentation
