Introduction
Programming languages are growing, this growth is due to the expansion in technology; with the emergence of the latest programming languages, new programming techniques are used to solve problems. There exist many problems, and these problems are solved using an enhanced programming paradigm. When the problem is from the domain of Artificial Intelligence, then choosing a programming language to solve the Artificial Intelligence problem must be based on well-established and tested heuristics.
Artificial Intelligence is the future of intelligent programming. Selecting a programming language for Artificial Intelligence is a challenging task because of the insufficient information available. Instead of selecting a programming language that you like the most, one should select a programming language that aligns with the programming objective.
The programmer must have an understanding of all the objectives to be achieved through programming. For example, the programmer must understand what is going to be the output of the program? What are the applications that the program is going to interact with? How long will the developed application be used? For which device is the application being developed? Whether the application under construction a web-based application or is it a web app?
If it is clear what is being developed and what will be the contribution of the developed application and what are the possible types of interactions that the developed application is going to have, then the question arises what should be the language that should be used to develop the desired application.
To choose a particular language, the programmer must do a comparative study to know the strength and weaknesses of the language is selected. The selected language must align with the desired objective. The language options narrow down to one when the software application and the objectives are finalized.
The language to develop an application having artificial intelligence in it must be efficient, and the grammar of the language must be such that it should meet up the functionality of the desired application. There should be predefined characteristics on the basis of which a particular language must be selected for an Artificial Intelligence-based application.
Characteristics to be Considered
There are many characteristics that must be considered before choosing a particular language for the development of the artificial intelligence-based application. If the Artificial-Intelligence-based application is a web-based application, then the programming language to be used must be a language that supports web intricacies. To develop a web application, a programmer can use Active Server Pages or Java Server Pages. In contrast, another programmer can use PHP or some other language that supports web-based applications.
Projecting one language for developing an application is difficult, but certain characteristics can be considered on the basis of which the language can be projected. These characteristics include the performance of the language in similar applications, security features of the language, and the strength of the inbuilt libraries that language has.
If the inbuilt library of the language has vast coverage of different functionalities, then it contributes to reducing the number of lines of code that in turn reduces the execution time of the code.
The programmer must select the programming language that should have the functionality to combine codes developed by different developers. This feature is used when the application being developed is under a Team, and team members are located distantly; in this, all members develop a particular functionality of the code and synchronize all the developed functionalities. Thus language used to develop the application must support Teamwork.
If the language selection is appropriate, then the resulting code is concise, debug friendly, the developed code is extensible, the language selection also influences documentation of the application being developed, and code migration is easy.
To select appropriate language following factors must be considered:
The Platform
It is critical to understand the importance of the platform on which the developed application will run. The language must be chosen that should be platform-independent. If the application is web-based, then the application should have the same appearance, and all the functionalities must work in the same manner across all the browsers. It is possible that the same language may provide a bit different appearance and a bit difference in the functionalities on different browsers. Thus browser compatibility must be checked for the selected language.
Language Extensibility
Language extensibility enables a programmer to extend the code when required. This is required when new features are needed to be added to the developed application. The most critical aspect of adding a new feature is that the language used to develop the application has an in-built library that can support the added feature. If the inbuilt library is not available, then the language must support the functionality using which new library can be included in the language? Is the language capable of meeting up the future requirements?
The Turnaround Time
The turnaround time of the application under development must be less. This time is directly influenced by the code size. Code size depends on the language.
Language Performance
The language must be selected such that its performance is the same in different computing environments. To compare the performance of different languages, different benchmarks have been developed. Language performance is one of the critical factors to be considered when the platform on which the application is being developed is hardbound and does not provide extensibility.
Technical Support of the Language
A language must have strong technical support. The technical support can be in the form of a community and a forum. The forums such as Blogs, Tutorials, Wikis, and Tutorials are good sources of technical support; in addition to this, rich sources of libraries are also good sources of technical support.
Objective
The objective is also an important aspect of selecting the appropriate language. If the application is being developed at the commercial level and the web-based interface is not required then a programming language such as COBOL, C and C++ is an appropriate choice.
If the language is being used for developing scientific applications then the programming languages such as ALGOL, FORTRAN, MATLAB, and R are significant.
For applications that handle the functionalities related to Artificial Intelligence than programming languages such as Python, LISP, Java, R are suitable.
If the application being developed is web-based then Object-Oriented language is the best choice.
If system-level programming has to be carried out then a programming language such as C is the best choice.
Working Knowledge of Developer
The selection of a particular programming language also depends on the professional working experience of the development team. If the development team is proficient in a particular language then that language should be used for the development of the target applications.
Reusability and Inheritance
The programming language must be selected, which provides the feature of reusability and inheritance. It should be possible to reuse the code of the application being developed with the help of inheritance. Inheritance improves the turnaround time of the application. It also helps programmers to add extra functionality to the application if required.
To achieve inheritance and reusability, Object-Oriented Programming languages are used instead of Procedural Languages.
Language Efficiency
The programming language chosen to develop a particular application should be efficient. Language should be selected whose execution time is fast. The efficiency of the language is also measured in terms of the total amount of memory required to execute the developed application. Those languages that consume less amount of memory to execute developed applications must be chosen for the development of the desired software application.
Development Environment
The environment in which the application is developed is also a critical factor in the selection of the programming language. The environment is decided by the language. Each language has its own development environment. The well-structured and properly designed development environment helps programmers to do efficient coding.
Debugging
Debugging is the process using which errors are localized, found, and removed. The selected programming language must have an efficient debugging feature. Debugging is the most critical aspect of program development. That programming language must be selected in which the technique of finding and removing errors is easy for the developers.
The Best Programming Language for Artificial Intelligence
Artificial Intelligence has its own intricacies that make it powerful to do things much as humans do and, in some cases, even more accurate than humans. Thus, Artificial Intelligence involves procedures, principles, and techniques that are used to instruct machines to make them work much like humans and in some cases, even better than humans.
To make machines work, they need to be instructed, and these instructions are given using a programming language. There exist many programming languages, and choosing the best among them is critical.
Programming languages that are available to instruct machines and make them do things and implement the procedure, principles, and techniques of Artificial Intelligence are Python, R, Prolog, Java, C++, and LISP.
Python
Python is one of the best programming languages to implement procedures, principles, and techniques of AI. Python is simple, flexible, and scalable. Python is an Open Source programming language. Python can be modified as required. The programming language for AI must be evolving in nature, and its syntax must be flexible, easier, and modifiable so that the efficiency of the programming language increases.
The libraries in Python for AI are readily available. For example, TensorFlow is an AI library that is most used for machine learning applications. PyTorch is another library that is available for natural language processing and computer vision.
All the applications that are developed in Python are platform-independent, and it gets attached with AI programming languages easily.
R
R is another programming language that is available for Artificial Intelligence. R is used for data analysis. R has inbuilt libraries that are available for machine learning and data mining.
Prolog
Prolog is a programming language that is also used to implement procedures, principles, and techniques of Artificial Intelligence. Prolog is used to do logic programming. Prolog is more intensively used to do programming in natural language processing. Prolog is also a language to be used for machine learning programming. The use of prolog is also found in the domain of expert systems.
Java
Java is also one of the programming languages that is used to implement procedures, principles, and techniques of Artificial Intelligence.
Java has an inbuilt machine learning library. Java is also used to implement procedures, principles, and techniques of Artificial Intelligence to make robots.
C++
C++ is also a programming language that can be used to implement procedures, principles, and techniques of Artificial Intelligence. C++ has libraries such as TensorFlow, Microsoft Cognitive Toolkit, Caffe, and DyNet. All these libraries are written in C++ and can be used for Machine learning. Being written in C++, these libraries provide fast execution cycles.
Thus, C++ is also one of the options for doing programming in Artificial Intelligence.
Which is not the commonly used Programming Language for AI
C++ is the only language that is not commonly used for implementing procedures, principles, and techniques of Artificial Intelligence.
Conclusion
The selection of appropriate AI language is critical. AI languages are used to make decisions based on a pattern that exists in the data. AI languages develop a heuristic on the basis of the pattern that exists in the data taken under study. Heuristics are developed to treat data. Using these heuristics algorithms are developed to process required information in order to imitate the intelligence of human beings. Processing information requires abstraction, and this is possible by using languages that are specially designed to work for Artificial Intelligence.
AI tries to imitate human cognitive science by processing natural language, mapping human vision to computer vision, and developing adaptable systems. An intense specification analysis is done to imitate human science in AI. This is not possible in one attempt. It is a rigorous and iterative process and improves with each iteration. In each iteration, interaction with the domain expert and subject under study is done. In AI, heuristics are developed using rapid proto-typing approaches.
A language must be selected in such a way that uses a data structure that enables AI programmers to associate data and establish a link between them, and AI programmers are more interested in using language that offers this type of data structure, such as trees. AI programming deals with the matching of patterns based on pre-specified or developed criteria. Those languages are used AI programming that supports pattern matching. Standard languages such as C language, Pascal language, and FORTRAN language miss in these types of abstractions such as binary trees and rigorous pattern matching.
To overcome these programming languages, two types of programming paradigms are used first, functional, and second, logical.
LISP is the most used functional AI programming language. The LISP programming language is based on function theory falling within the domain of mathematics. LISP also uses Lambda theory which is based on the theory of lambda. LISP programming languages are used in many AI applications.
Prolog is the most used logic AI programming language. Logic AI programming language is based on predicate calculus. Prolog uses rules that are logical, axioms, and related facts. Prolog also uses procedures and principles of theorem proving.
The least used AI programming language is C++. C++ is another object-oriented programming language that is used AI programming. C++ allows using abstract data structures known as objects and classes. Class is an encapsulation of data members and member functions. Classes can be divided into sub-categories and support the concept of inheritance. Thus a class can be arranged hierarchically.
Two of the known Object-Oriented programming languages are C++ and Java. Java is also used few AI applications. Java has found its application in intelligent agents, searching and finding on the internet and conducting data mining to find patterns. J++ has its root in C++ and is extensively used on the Internet. Java supports automatic garbage collection and multi-threading that is extensively used in AI applications. Java intelligence is used to interact with the users on the internet. Java intelligent agents are used to provide the next step to be processed to users surfing the website and for intelligent do not have to interact with the user they only had to make decisions on the heuristics. Although Java has many features that make it useful for AI programming then also it is the least used AI programming language.
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