Computer architecture 7MB#^H8cC
Computer networks FZ._ n!boM
Distributed computing
Performance of systems
Computer system implementation y(V"Ch.l
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Software
Computer program and Computer programming U5oP:p4sR+u
Concurrent Programming
Parallel Programming
Program specification
Structured programming
Programming languages o(OmV8E}z
Imperative programming Languages such as C
Functional programming Languages such as LISP
Logic programming Languages such as Prolog S(]+vc4]'L f"`z
Operating Systems "u"`@wbw
Compilers
Lexical analysis
Parsing *M(\oD6{}RH
Data structures &g)kn.K2D]Y/iV+y7TU
Data storage representations P5Qm:dVE+T
Data encryption
Data compression
Data recovery (l*^#_6J9mt$W
Coding and Information theory
Files
Information Storage and retrieval
Information Interfaces and Presentation
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Personal computing d4i)Am(jQ"b!{}} Q'P/q
History of computing T-p#`^AqO`
Origins of computer terms
Early programming projects /t6|#RQ|)AN2I+Ex
Computer science departments
Timeline of algorithms GVb)B4v
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Prominent pioneers in computer science
Person Achievement
John Vincent Atanasoff Built an electronic digital computer: the ABC Computer. Unlike ENIAC, the first all-electronic computer designed to be Turing-complete, the ABC Computer was not programmable.
Charles Babbage Designed and built a prototype for a mechanical calculator and designed the more powerful Analytical Engine. c:e~|P8P
John Backus Invented FORTRAN (Formula Translation), the first practical high-level programming language, and he formulated the Backus-Naur form that described the formal language syntax.
George Boole Formalized boolean algebra, the basis for digital logic and computer science.

John Mauchly and J. Presper Eckert Designed and built the ENIAC, the first all electronic Turing-complete computer, and the UNIVAC I, the first commercially available computer in the United States. John von Neumann of the Institute for Advanced Study admitted to being greatly influenced by their work when he did pioneering work in computer architecture.
John McCarthy Invented LISP, a functional programming language. b8P+rf A~
John von Neumann Devised the von Neumann architecture upon which most modern computers are based.
Claude E. Shannon Founded information theory. [W8@:qz T
Emil L. Post Developed the Post machine as a model of computation, independently of Turing. Known also for developing truth tables, the Post correspondence problem used in recursion theory as well as proving what is knows as Post's theorem. w{}2Bs2P
1 History :C9m-A)Y5~#O9F
1.1 Prehistory of AI
1.2 Development of AI theory
1.3 Experimental AI research
2 Modern AI
3 Micro-World AI O"l;TX2woh
4 Languages, Programming Style and Software Culture
5 AI research in various countries
5.1 United Kingdom
6 AI in Business g;t)v~)nMz
7 Machines displaying some degree of intelligence
8 AI Researchers
9 Further reading ~~9o(jt
9.1 Non-fiction

11.1 General \Wh+j eecivv
11.2 AI related organizations 3kgVc|u Q[i

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History
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Prehistory of AI
Humans have always speculated about the nature of mind, thought, and language, and searched for discrete representations of their knowledge. Aristotle tried to formalize this speculation by means of syllogistic logic, which remains one of the key strategies of AI. The first is-a hierarchy was created in 260 by Porphyry of Tyros. Classical and medieval grammarians explored more subtle features of language that Aristotle shortchanged, and mathematician Bernard Bolzano made the first modern attempt to formalize semantics in 1837.

Early computer design was driven mainly by the complex mathematics needed to target weapons accurately, with analog feedback devices inspiring an ideal of cybernetics. The expression "artificial intelligence" was introduced as a 'digital' replacement for the analog 'cybernetics'.

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Development of AI theoryh-j'j/\1h#E1i
Much of the (original) focus of artificial intelligence research draws from an experimental approach to psychology, and emphasizes what may be called linguistic intelligence (best exemplified in the Turing test).mJ+yXm%{}eq M*`r|
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Modern AI research focuses on practical engineering tasks. (Supporters of Strong AI may call this approach 'weak AI'.)

There are several fields of AI, one of which is natural language. Many weak AI fields have specialised software or programming languages created for them. For example, one of the 'most-human' natural language chatterbots, A.L.I.C.E., uses a programming language AIML that is specific to its program, and the various clones, named Alicebots. Nevertheless, A.L.I.C.E. is still based on pattern matching without any reasoning. This is the same technique Eliza, the first chatterbot, was using back in 1966. Jabberwacky is a little closer to strong AI, since it learns how to converse from the ground up based solely on user interactions. In spite of that, the result is still very poor, and it is reasonable to state that there is actually no general purpose conversational artificial intelligence./_,PdQ(IS-mS
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When viewed with a moderate dose of cynicism, AI can be viewed as ‘the set of computer science problems without good solutions at this point’. Once a sub-discipline results in useful work, it is carved out of artificial intelligence and given its own name. Examples of this are pattern recognition, image processing, neural networks, natural language processing, robotics and game theory. While the roots of each of these disciplines is firmly established as having been part of artificial intelligence, they are now thought of as somewhat separate.;I"vF2\^ ud
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AI planning methods were used to automatically plan the deployment of US forces during Gulf War I. This task would have cost months of time and millions of dollars to perform manually, and DARPA stated that the money saved on this single application was more than their total expenditure on AI research over the last 30 years. W*@9r+s5M
The vision of artificial intelligence replacing human professional judgment has arisen many times in the history of the field, and today in some specialized areas where "expert systems" are routinely used to augment or to replace professional judgment in some areas of engineering and of medicine. An example of an expert system is Clippy the paperclip in Microsoft Office which tried to predict what advice the user would like.:VU:Z/f4_
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Micro-World AI