Symbolic Programming
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Symbolic Programming
In computer programming, symbolic programming is a programming paradigm in which the program can manipulate its own formulas and program components as if they were plain data. Through symbolic programming, complex processes can be developed that build other more intricate processes by combining smaller units of logic or functionality. Thus, such programs can effectively modify themselves and appear to "learn", which makes them better suited for applications such as artificial intelligence, expert systems, natural language processing, and computer games. Languages that support symbolic programming include homoiconic languages such as Wolfram Language, LISP and Prolog. See also *Symbolic artificial intelligence *Symbolic language (programming) In computer science, a symbolic language is a language that uses Character (computing), characters or symbols to represent concepts, such as Operation (mathematics), mathematical operations and the entities (or operands) on which these operat ...
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Computer Programming
Computer programming is the process of performing a particular computation (or more generally, accomplishing a specific computing result), usually by designing and building an executable computer program. Programming involves tasks such as analysis, generating algorithms, profiling algorithms' accuracy and resource consumption, and the implementation of algorithms (usually in a chosen programming language, commonly referred to as coding). The source code of a program is written in one or more languages that are intelligible to programmers, rather than machine code, which is directly executed by the central processing unit. The purpose of programming is to find a sequence of instructions that will automate the performance of a task (which can be as complex as an operating system) on a computer, often for solving a given problem. Proficient programming thus usually requires expertise in several different subjects, including knowledge of the application domain, specialized algori ...
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Programming Paradigm
Programming paradigms are a way to classify programming languages based on their features. Languages can be classified into multiple paradigms. Some paradigms are concerned mainly with implications for the execution model of the language, such as allowing side effects, or whether the sequence of operations is defined by the execution model. Other paradigms are concerned mainly with the way that code is organized, such as grouping a code into units along with the state that is modified by the code. Yet others are concerned mainly with the style of syntax and grammar. Common programming paradigms include: * imperative in which the programmer instructs the machine how to change its state, ** procedural which groups instructions into procedures, ** object-oriented which groups instructions with the part of the state they operate on, * declarative in which the programmer merely declares properties of the desired result, but not how to compute it ** functional in which the de ...
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Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ...
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Expert Systems
In artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of artificial intelligence (AI) software. An expert system is divided into two subsystems: the inference engine and the knowledge base. The knowledge base represents facts and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging abilities. History Early development Soon after the dawn of modern computers in the late 1940s and early 1950s, researchers started realizing the immense potential these machines had for modern society. One of ...
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Natural Language Processing
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves. Challenges in natural language processing frequently involve speech recognition, natural-language understanding, and natural-language generation. History Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, t ...
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Homoiconic
In computer programming, homoiconicity (from the Greek words ''homo-'' meaning "the same" and ''icon'' meaning "representation") is a property of some programming languages. A language is homoiconic if a program written in it can be manipulated as data using the language, and thus the program's internal representation can be inferred just by reading the program itself. This property is often summarized by saying that the language treats "code as data". In a homoiconic language, the primary representation of programs is also a data structure in a primitive type of the language itself. This makes metaprogramming easier than in a language without this property: reflection in the language (examining the program's entities at runtime) depends on a single, homogeneous structure, and it does not have to handle several different structures that would appear in a complex syntax. Homoiconic languages typically include full support of syntactic macros, allowing the programmer to express tr ...
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Wolfram Language
The Wolfram Language ( ) is a general multi-paradigm programming language developed by Wolfram Research. It emphasizes symbolic computation, functional programming, and rule-based programming and can employ arbitrary structures and data. It is the programming language of the mathematical symbolic computation program Mathematica. History The Wolfram Language was a part of the initial version of Mathematica in 1988. Symbolic aspects of the engine make it a computer algebra system. The language can perform integration, differentiation, matrix manipulations, and solve differential equations using a set of rules. Also, the initial version introduced the notebook model and the ability to embed sound and images, according to Theodore Gray's patent. Wolfram also added features for more complex tasks, such as 3D modeling. A name was finally adopted for the language in 2013, as Wolfram Research decided to make a version of the language engine free for Raspberry Pi users, and they need ...
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LISP
A lisp is a speech impairment in which a person misarticulates sibilants (, , , , , , , ). These misarticulations often result in unclear speech. Types * A frontal lisp occurs when the tongue is placed anterior to the target. Interdental lisping is produced when the tip of the tongue protrudes between the front teeth and dentalized lisping is produced when the tip of the tongue just touches the front teeth. The transcription in the International Phonetic Alphabet for interdental sibilants is and and for simple dental sibilants is and . When a fronted lisp does not have a sibilant quality, due to placing the lack of a grooved articulation, the IPA transcription would be or variants thereof. * A occurs when the and sounds are produced with air-flow over the sides of the tongue. It is also called "slushy ess" or a "slushy lisp" in part due to its wet, spitty sound. The symbols for these lateralised sounds in the extensions to the International Phonetic Alphabet for disordere ...
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Prolog
Prolog is a logic programming language associated with artificial intelligence and computational linguistics. 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 logic is expressed in terms of relations, represented as facts and rules. A computation is initiated by running a ''query'' over these relations. The language was developed and implemented in Marseille, France, in 1972 by Alain Colmerauer with Philippe Roussel, based on Robert Kowalski's procedural interpretation of Horn clauses at University of Edinburgh. Prolog was one of the first logic programming languages and remains the most popular such language today, with several free and commercial implementations available. The language has been used for theorem proving, expert systems, term rewriting, type systems, and automated planning, as well as its original intended field of use, nat ...
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Symbolic Artificial Intelligence
In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems (in particular, expert systems), symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. The Symbolic AI paradigm led to seminal ideas in search, symbolic programming languages, agents, multi-agent systems, the semantic web, and the strengths and limitations of formal knowledge and reasoning systems. Symbolic AI was the dominant paradigm of AI research from the mid-1950s until the middle 1990s. Researchers in the 1960s and the 1970s were convinced that symbolic approaches would eventually succeed in creating ...
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Symbolic Language (programming)
In computer science, a symbolic language is a language that uses Character (computing), characters or symbols to represent concepts, such as Operation (mathematics), mathematical operations and the entities (or operands) on which these operations are performed. Modern programming languages use symbols to represent concepts and/or data and are therefore, examples of symbolic languages. Some programming languages (such as Lisp (programming language), Lisp and Wolfram Mathematica, Mathematica) make it easy to represent higher-level Abstraction (computer science), abstractions as Expression (computer science), expressions in the language, enabling symbolic programming., See also *Mathematical notation *Notation, Notation (general) *Programming language specification *Symbol table *Symbolic language (other), Symbolic language (other) References External links Common LISP: A Gentle Introduction to Symbolic Computation
- Carnegie Mellon University {{DEFAULTSORT:Symbolic ...
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