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Python is a high-level, general-purpose programming language that is popular in artificial intelligence. [1] It has a simple, flexible and easily readable syntax. [2] Its popularity results in a vast ecosystem of libraries, including for deep learning, such as PyTorch, TensorFlow, Keras, Google JAX.
Prolog is a logic programming language that has its origins in artificial intelligence, automated theorem proving and computational linguistics. [1] [2] [3]Prolog has its roots in first-order logic, a formal logic, and unlike many other programming languages, Prolog is intended primarily as a declarative programming language: the program is a set of facts and rules, which define relations.
Fifth-generation languages are used mainly in artificial intelligence research. OPS5 and Mercury are examples of fifth-generation languages, [2] as is ICAD, which was built upon Lisp. KL-ONE is an example of a related idea, a frame language.
For other AI programming languages see this list of programming languages for artificial intelligence. Currently, Python, a multi-paradigm programming language, is the most popular programming language, partly due to its extensive package library that supports data science, natural language processing, and deep learning.
It quickly became a favored programming language for artificial intelligence (AI) research. [10] As one of the earliest programming languages, Lisp pioneered many ideas in computer science , including tree data structures , automatic storage management , dynamic typing , conditionals , higher-order functions , recursion , the self-hosting ...
4 Programming examples. ... It was selected as Programming Language of the Year ... Python is commonly used in artificial intelligence projects and machine learning ...
TensorFlow is a software library for machine learning and artificial intelligence. It can be used across a range of tasks, but is used mainly for training and inference of neural networks. [3] [4] It is one of the most popular deep learning frameworks, alongside others such as PyTorch and PaddlePaddle.
An early example of answer set programming was the planning method proposed in 1997 by Dimopoulos, Nebel and Köhler. [3] [4] Their approach is based on the relationship between plans and stable models. [5] In 1998 Soininen and Niemelä [6] applied what is now known as answer set programming to the problem of product configuration. [4]
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