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.
Highlights
Artificial Intelligence (AI) is concerned with intelligent behaviors in artifacts such as perception, reasoning, learning, communicating and acting in a complex environment
Our search returned 7,604 documents related to AI programming languages; Scopus (5,818) and IEEE Xplore (435)
Of the 7,170 documents remaining, 6,665 documents were excluded based on the following criteria; studies that do not relate to Artificial Intelligence programming languages and reviews, books, book chapters, reports, notes, short survey, letter, viewpoints and editorials
Summary
Artificial Intelligence (AI) is concerned with intelligent behaviors in artifacts such as perception, reasoning, learning, communicating and acting in a complex environment. AI involves the science and engineering of machines that possess the listed characteristics, which humans can do, better and faster. A physical symbol system is a machine like a digital computer capable of manipulating symbolic dataadding numbers, rearranging lists of symbols and replacing some symbols with others (Nilsson, 2010). Computing is used for performing mechanical computations using fixed procedures. This approach implies complex problems would be more difficult to solve. Another shortcoming is that computers so programmed would have difficulties understanding and adapting to new situations as humans do. AI is different from this traditional approach in that it requires machines to think and tackle such complex assignments. AI was formally coined by John McCarthy in a workshop conducted by IBM at Dartmouth College in 1956 (Nilsson and Nilsson,1998)
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