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SubL
Cyc (pronounced ) is a long-term artificial intelligence (AI) project that aims to assemble a comprehensive ontology (information science), ontology and knowledge base that spans the basic concepts and rules about how the world works. Hoping to capture common sense knowledge, Cyc focuses on implicit knowledge. The project began in July 1984 at Microelectronics and Computer Technology Corporation, MCC and was developed later by the Cycorp company. The name "Cyc" (from "encyclopedia") is a registered trademark owned by Cycorp. CycL has a publicly released specification, and dozens of HL (Heuristic Level) modules were described in Lenat and Guha's textbook, but the Cyc inference engine code and the full list of HL modules are Cycorp-proprietary. History The project began in July 1984 by Douglas Lenat as a project of the Microelectronics and Computer Technology Corporation (MCC), a research consortium started by two United States–based corporations "to counter a then ominous Japa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Douglas Lenat
Douglas Bruce Lenat (September 13, 1950 – August 31, 2023) was an American computer scientist and researcher in artificial intelligence who was the founder and CEO of Cycorp, Inc. in Austin, Texas. Lenat was awarded the biannual IJCAI Computers and Thought Award in 1976 for creating the machine-learning program AM. He has worked on (symbolic, not statistical) machine learning (with his AM and Eurisko programs), knowledge representation, "cognitive economy", blackboard systems, and what he dubbed in 1984 " ontological engineering" (with his Cyc program at MCC and, since 1994, at Cycorp). He has also worked in military simulations, and numerous projects for the US government, military, intelligence, and scientific organizations. In 1980, he published a critique of conventional random-mutation Darwinism. He authored a series of articles in the Journal of Artificial Intelligence exploring the nature of heuristic rules. Lenat was one of the original Fellows of the A ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Russell Greiner
Russell Greiner is a professor of computing science at the University of Alberta. He is a fellow of the Association for the Advancement of Artificial Intelligence and a specialist in machine learning and bioinformatics. Greiner is one of the principal investigators at the Alberta Innovates Centre for Machine Learning and has published over 200 refereed papers and patents. After earning a PhD from Stanford University, Greiner worked in both academic and industrial research before settling at the University of Alberta, where he became a professor in Computing Science (adjunct in Psychiatry) and the founding scientific director of the Alberta Machine Intelligence Institute. He was elected Fellow of the AAAI(Association for the Advancement of Artificial Intelligence The Association for the Advancement of Artificial Intelligence (AAAI) is an international Learned society, scientific society devoted to promote research in, and responsible use of, artificial intelligence. AAAI also ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Abductive Reasoning
Abductive reasoning (also called abduction,For example: abductive inference, or retroduction) is a form of logical inference that seeks the simplest and most likely conclusion from a set of observations. It was formulated and advanced by American philosopher and logician Charles Sanders Peirce beginning in the latter half of the 19th century. Abductive reasoning, unlike deductive reasoning, yields a plausible conclusion but does not definitively verify it. Abductive conclusions do not eliminate uncertainty or doubt, which is expressed in terms such as "best available" or "most likely". While inductive reasoning draws general conclusions that apply to many situations, abductive conclusions are confined to the particular observations in question. In the 1990s, as computing power grew, the fields of law, computer science, and artificial intelligence researchFor examples, see "", John R. Josephson, Laboratory for Artificial Intelligence Research, Ohio State University, and ''Abduc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Symbolic Artificial Intelligence
Symbolic may refer to: * Symbol, something that represents an idea, a process, or a physical entity Mathematics, logic, and computing * Symbolic computation, a scientific area concerned with computing with mathematical formulas * Symbolic dynamics, a method for modeling dynamical systems by a discrete space consisting of infinite sequences of abstract symbols * Symbolic execution, the analysis of computer programs by tracking symbolic rather than actual values * Symbolic link, a special type of file in a computer memory storage system * Symbolic logic, the use of symbols for logical operations in logic and mathematics Music * Symbolic (Death album), ''Symbolic'' (Death album), a 1995 album by the band Death * Symbolic (Voodoo Glow Skulls album), ''Symbolic'' (Voodoo Glow Skulls album), a 2000 album by the band Voodoo Glow Skulls Social sciences * Symbolic anthropology, the study of cultural symbols and how those symbols can be interpreted to better understand a particular society ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Learning Theory
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as computer vision, speech recognition, and bioinformatics. Introduction The goals of learning are understanding and prediction. Learning falls into many categories, including supervised learning, unsupervised learning, online learning, and reinforcement learning. From the perspective of statistical learning theory, supervised learning is best understood. Supervised learning involves learning from a training set of data. Every point in the training is an input–output pair, where the input maps to an output. The learning problem consists of inferring the function that maps between the input and the output, such that the learned function can be used to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inductive Reasoning
Inductive reasoning refers to a variety of method of reasoning, methods of reasoning in which the conclusion of an argument is supported not with deductive certainty, but with some degree of probability. Unlike Deductive reasoning, ''deductive'' reasoning (such as mathematical induction), where the conclusion is ''certain'', given the premises are correct, inductive reasoning produces conclusions that are at best ''probable'', given the evidence provided. Types The types of inductive reasoning include generalization, prediction, statistical syllogism, argument from analogy, and causal inference. There are also differences in how their results are regarded. Inductive generalization A generalization (more accurately, an ''inductive generalization'') proceeds from premises about a Sample (statistics), sample to a conclusion about the statistical population, population. The observation obtained from this sample is projected onto the broader population. : The proportion Q of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Logical Deduction
Deductive reasoning is the process of drawing valid inferences. An inference is valid if its conclusion follows logically from its premises, meaning that it is impossible for the premises to be true and the conclusion to be false. For example, the inference from the premises "all men are mortal" and "Socrates is a man" to the conclusion "Socrates is mortal" is deductively valid. An argument is ''sound'' if it is valid ''and'' all its premises are true. One approach defines deduction in terms of the intentions of the author: they have to intend for the premises to offer deductive support to the conclusion. With the help of this modification, it is possible to distinguish valid from invalid deductive reasoning: it is invalid if the author's belief about the deductive support is false, but even invalid deductive reasoning is a form of deductive reasoning. Deductive logic studies under what conditions an argument is valid. According to the semantic approach, an argument is valid if th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Chordate
A chordate ( ) is a bilaterian animal belonging to the phylum Chordata ( ). All chordates possess, at some point during their larval or adult stages, five distinctive physical characteristics ( synapomorphies) that distinguish them from other taxa. These five synapomorphies are a notochord, a hollow dorsal nerve cord, an endostyle or thyroid, pharyngeal slits, and a post- anal tail. In addition to the morphological characteristics used to define chordates, analysis of genome sequences has identified two conserved signature indels (CSIs) in their proteins: cyclophilin-like protein and inner mitochondrial membrane protease ATP23, which are exclusively shared by all vertebrates, tunicates and cephalochordates. These CSIs provide molecular means to reliably distinguish chordates from all other animals. Chordates are divided into three subphyla: Vertebrata (fish, amphibians, reptiles, birds and mammals), whose notochords are replaced by a cartilaginous/ bony axia ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sibling
A sibling is a relative that shares at least one parent with the other person. A male sibling is a brother, and a female sibling is a sister. A person with no siblings is an only child. While some circumstances can cause siblings to be raised separately (such as foster care or adoption), most societies have siblings grow up together. This causes the development of strong emotional bonds, with siblinghood considered a unique type of relationship. The emotional bond between siblings is often complicated and is influenced by factors such as parental treatment, birth order, personality, and personal experiences outside the family. Medically, a full-sibling is a first-degree relative and a half-sibling is a second-degree relative as they are related by 50% and 25%, respectively. Definitions The word ''sibling'' was reintroduced in 1903 in an article in '' Biometrika'', as a translation for the German ''Geschwister'', having not been used since Middle English, specifically 142 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Equivalence Relation
In mathematics, an equivalence relation is a binary relation that is reflexive, symmetric, and transitive. The equipollence relation between line segments in geometry is a common example of an equivalence relation. A simpler example is equality. Any number a is equal to itself (reflexive). If a = b, then b = a (symmetric). If a = b and b = c, then a = c (transitive). Each equivalence relation provides a partition of the underlying set into disjoint equivalence classes. Two elements of the given set are equivalent to each other if and only if they belong to the same equivalence class. Notation Various notations are used in the literature to denote that two elements a and b of a set are equivalent with respect to an equivalence relation R; the most common are "a \sim b" and "", which are used when R is implicit, and variations of "a \sim_R b", "", or "" to specify R explicitly. Non-equivalence may be written "" or "a \not\equiv b". Definitions A binary relation \,\si ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Wikidata
Wikidata is a collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation. It is a common source of open data that Wikimedia projects such as Wikipedia, and anyone else, are able to use under the CC0 public domain license. Wikidata is a wiki powered by the software MediaWiki, including its extension for semi-structured data, the Wikibase. As of early 2025, Wikidata had 1.65 billion item statements ( semantic triples). Concept Wikidata is a document-oriented database, focusing on ''items'', which represent any kind of topic, concept, or object. Each item is allocated a unique persistent identifier called its ''QID'', a positive integer prefixed with the upper-case letter "Q". This makes it possible to provide translations of the basic information describing the topic each item covers without favouring any particular language. Some examples of items and their QIDs are , , , , and . Item ''labels'' do not need to be unique. For example, th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
