Evolution of Artificial Intelligence Programming Languages - a Systematic Literature Review

Abstract

Artificial Intelligence (AI) has received significant attention in recent years. It is being adopted to provide solutions to medicine, engineering, education, government and several other domains. To analyze the state-of-the-art of research in AI, we present a systematic literature review focusing on the Evolution of AI programming languages. Our search returned 7,604 documents; after reviewing these documents, 78 which were relevant for this study were retained. Our research revealed that the prevalence of AI programming language by volume of publications had experienced peaks and valleys between 1963 and 2018; however, between 2015 to 2020, related publications have been experiencing peaks. During the review period, the PROLOG programming language received the most attention in about 49% of publications; this was followed by LISP, which received almost 22%. The remaining attention was shared between Logic and Object-Oriented Programming (LOOP), ARCHLOG, Epistemic Ontology Language with Constraints (EOLC), Python, C++, ADA and JAVA. However, the predominant AI programming language in recent AI software is C/C++, which takes 70% of the modern AI libraries analyzed in this study. Python is used in 60% of the modern AI libraries analyzed. Their prevalence is as a result of their speed, portability and ease of coding, making them effective in developing trending AI libraries such as TensorFlow and Keras.