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Inference Engine
In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine. The knowledge base stored facts about the world. The inference engine applied logical rules to the knowledge base and deduced new knowledge. This process would iterate as each new fact in the knowledge base could trigger additional rules in the inference engine. Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward chaining starts with the known facts and asserts new facts. Backward chaining starts with goals, and works backward to determine what facts must be asserted so that the goals can be achieved. Additionally, the concept of 'inference' has expanded to include the process t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to machine perception, perceive their environment and use machine learning, learning and intelligence to take actions that maximize their chances of achieving defined goals. High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon (company), Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Amazon Alexa, Alexa); autonomous vehicles (e.g., Waymo); Generative artificial intelligence, generative and Computational creativity, creative tools (e.g., ChatGPT and AI art); and Superintelligence, superhuman play and analysis in strategy games (e.g., ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Interpreted Language
In computer science, an interpreter is a computer program that directly executes instructions written in a programming or scripting language, without requiring them previously to have been compiled into a machine language program. An interpreter generally uses one of the following strategies for program execution: # Parse the source code and perform its behavior directly; # Translate source code into some efficient intermediate representation or object code and immediately execute that; # Explicitly execute stored precompiled bytecode made by a compiler and matched with the interpreter's virtual machine. Early versions of Lisp programming language and minicomputer and microcomputer BASIC dialects would be examples of the first type. Perl, Raku, Python, MATLAB, and Ruby are examples of the second, while UCSD Pascal is an example of the third type. Source programs are compiled ahead of time and stored as machine independent code, which is then linked at run- ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Backward Chaining
Backward chaining (or backward reasoning) is an inference method described colloquially as working backward from the goal. It is used in automated theorem provers, inference engines, proof assistants, and other artificial intelligence applications. In game theory, researchers apply it to (simpler) subgames to find a solution to the game, in a process called ''backward induction''. In chess, it is called retrograde analysis, and it is used to generate table bases for chess endgames for computer chess. Backward chaining is implemented in logic programming by SLD resolution. Both rules are based on the modus ponens inference rule. It is one of the two most commonly used methods of reasoning with inference rules and logical implications – the other is forward chaining. Backward chaining systems usually employ a depth-first search strategy, e.g. Prolog. Usage Backward chaining starts with a list of goals (or a hypothesis) and works backwards from the consequent to the antec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Action Selection
Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behavior in an agent environment. The term is also sometimes used in ethology or animal behavior. One problem for understanding action selection is determining the level of abstraction used for specifying an "act". At the most basic level of abstraction, an atomic act could be anything from ''contracting a muscle cell'' to ''provoking a war''. Typically for any one action-selection mechanism, the set of possible actions is predefined and fixed. Most researchers working in this field place high demands on their agents: * The acting agent typically must select its action in dynamic and unpredictable environments. * The agents typically act in real time; therefore they must make ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Geometric And Topological Inference
''Geometric and Topological Inference'' is a monograph in computational geometry, computational topology, geometry processing, and topological data analysis, on the problem of inferring properties of an unknown space from a finite point cloud of noisy samples from the space. It was written by Jean-Daniel Boissonnat, Frédéric Chazal, and Mariette Yvinec, and published in 2018 by the Cambridge University Press in their Cambridge Texts in Applied Mathematics book series. The Basic Library List Committee of the Mathematical Association of America has suggested its inclusion in undergraduate mathematics libraries. Topics The book is subdivided into four parts and 11 chapters. The first part covers basic tools from topology needed in the study, including simplicial complexes, Čech complexes and Vietoris–Rips complex, homotopy equivalence of topological spaces to their nerves, filtrations of complexes, and the data structures needed to represent these concepts efficiently in co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Jacques Pitrat
Jacques Pitrat (born in Feb. 1934, died in Oct. 2019) was one of the French symbolic artificial intelligence pioneers. He developed knowledge based systems, expert systems, and theorem provers, and was a strong advocate of meta-knowledge based systems. Graduated from École Polytechnique, and member of the Corps de l'armement, he began his career at the Laboratoire Central de l'Armement (French equivalent of DARPA) from 1959 to 1967. In 1966 he defended his Habilitation thesis (Doctorat d'État) about a theorem proving software using meta-theorems. He worked at the CNRS from 1967 till his retirement, ending his career as emeritus research director at the end of 2015. He taught artificial intelligence at the Université Pierre et Marie Curie in Paris from 1967 till 1998. He was elected an AAAI Fellow Fellowship of the Association for the Advancement of Artificial Intelligence (abbreviated as AAAI Fellow or FAAAI) is an award granted to individuals that the Association for the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Personal Computer
A personal computer, commonly referred to as PC or computer, is a computer designed for individual use. It is typically used for tasks such as Word processor, word processing, web browser, internet browsing, email, multimedia playback, and PC game, gaming. Personal computers are intended to be operated directly by an end user, rather than by a computer expert or technician. Unlike large, costly minicomputers and mainframes, time-sharing by many people at the same time is not used with personal computers. The term home computer has also been used, primarily in the late 1970s and 1980s. The advent of personal computers and the concurrent Digital Revolution have significantly affected the lives of people. Institutional or corporate computer owners in the 1960s had to write their own programs to do any useful work with computers. While personal computer users may develop their applications, usually these systems run commercial software, free-of-charge software ("freeware"), which i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Edward Feigenbaum
Edward Albert Feigenbaum (born January 20, 1936) is a computer scientist working in the field of artificial intelligence, and joint winner of the 1994 ACM Turing Award. He is often called the "father of expert systems". Education and early life Feigenbaum was born in Weehawken, New Jersey in 1936 to a culturally Jewish family, and moved to nearby North Bergen, where he lived until the age of 16, when he left to start college. Knuth, Don"Oral History of Edward Feigenbaum'' Computer History Museum, 2007. Accessed October 23, 2015. "I was born in Weehawken, New Jersey, which is a town on the Palisades opposite New York. In fact, it’s the place where the Lincoln Tunnel dives under the water and comes up in New York. Then my parents moved up the Palisades four miles to a town called North Bergen, and there I lived until I was 16 and went off to Carnegie Tech." His hometown did not have a secondary school of its own, and so he chose Weehawken High School for its college preparatory ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
IntelliCorp (software)
IntelliCorp (IC) was an American software company based in Silicon Valley. It sold its assets including LiveCompare, LiveModel and LiveInterface to Tricentis in May 2019. History Founded in 1980, IC marketed an early expert system environment ( Knowledge Engineering Environment – KEE) for development and deployment of knowledge systems on the Lisp machines that had several advanced features, such as truth maintenance. KEE used the backward-chaining method of Mycin which had been developed at Stanford. While moving KEE functionality to the PC, IC created one of the early object-oriented technologies for commercial programming development environments (LiveModel). The company was also one of the UML Partners, a consortium which helped develop the standards for UML, the Unified Modeling Language The Unified Modeling Language (UML) is a general-purpose visual modeling language that is intended to provide a standard way to visualize the design of a system. UML provides a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prolog
Prolog is a logic programming language that has its origins in artificial intelligence, automated theorem proving, and computational linguistics. Prolog has its roots in first-order logic, a formal logic. Unlike many other programming languages, Prolog is intended primarily as a declarative programming language: the program is a set of facts and Horn clause, rules, which define Finitary relation, relations. A computation is initiated by running a ''query'' over the program. 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 automated theorem proving, theorem proving, expert systems, term rewriting, type systems, and automated planning, as well as its original intended field of use, natural language processing. See also Watson (computer). Prolog is a Turing-complete, general-purpose programming language, which is well-suited for inte ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rete Algorithm
The Rete algorithm ( , , rarely , ) is a pattern matching algorithm for implementing rule-based systems. The algorithm was developed to efficiently apply many rules or patterns to many objects, or facts, in a knowledge base. It is used to determine which of the system's rules should fire based on its data store, its facts. The Rete algorithm was designed by Charles L. Forgy of Carnegie Mellon University, first published in a working paper in 1974, and later elaborated in his 1979 Ph.D. thesis and a 1982 paper. Overview A naive implementation of an expert system might check each rule against known facts in a knowledge base, firing that rule if necessary, then moving on to the next rule (and looping back to the first rule when finished). For even moderate sized rules and facts knowledge-bases, this naive approach performs far too slowly. The Rete algorithm provides the basis for a more efficient implementation. A Rete-based expert system builds a network of nodes, where ea ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
OPS5
OPS5 is a rule-based or production system computer language, notable as the first such language to be used in a successful expert system, the R1/XCON system used to configure VAX computers. The OPS (said to be short for "Official Production System") family was developed in the late 1970s by Charles Forgy while at Carnegie Mellon University. Allen Newell's research group in artificial intelligence had been working on production systems for some time, but Forgy's implementation, based on his Rete algorithm, was especially efficient, sufficiently so that it was possible to scale up to larger problems involving hundreds or thousands of rules. OPS5 uses a forward chaining inference engine; programs execute by scanning "working memory elements" (which are vaguely object-like, with classes and attributes) looking for matches with the rules in "production memory". Rules have actions that may modify or remove the matched element, create new ones, perform side effects such as output, and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
