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Semantic Memory
Semantic memory refers to general world knowledge that humans have accumulated throughout their lives. This general knowledge (Semantics, word meanings, concepts, facts, and ideas) is intertwined in experience and dependent on culture. New concepts are learned by applying knowledge learned from things in the past. Semantic memory is distinct from episodic memory—the memory of experiences and specific events that occur in one's life that can be recreated at any given point. For instance, semantic memory might contain information about what a cat is, whereas episodic memory might contain a specific memory of stroking a particular cat. Semantic memory and episodic memory are both types of explicit memory, explicit memory (or declarative memory), or memory of facts or events that can be consciously recalled and "declared". The counterpart to declarative or explicit memory is implicit memory (also known as nondeclarative memory). History The idea of semantic memory was first intr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Knowledge
Knowledge is an Declarative knowledge, awareness of facts, a Knowledge by acquaintance, familiarity with individuals and situations, or a Procedural knowledge, practical skill. Knowledge of facts, also called propositional knowledge, is often characterized as Truth, true belief that is distinct from opinion or guesswork by virtue of Justification (epistemology), justification. While there is wide agreement among philosophers that propositional knowledge is a form of true belief, many controversies focus on justification. This includes questions like how to understand justification, whether it is needed at all, and whether something else besides it is needed. These controversies intensified in the latter half of the 20th century due to a series of thought experiments called ''Gettier cases'' that provoked alternative definitions. Knowledge can be produced in many ways. The main source of empirical knowledge is perception, which involves the usage of the senses to learn about ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Neural Network
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or signal pathways. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural networks. *In neuroscience, a '' biological neural network'' is a physical structure found in brains and complex nervous systems – a population of nerve cells connected by synapses. *In machine learning, an '' artificial neural network'' is a mathematical model used to approximate nonlinear functions. Artificial neural networks are used to solve artificial intelligence problems. In biology In the context of biology, a neural network is a population of biological neurons chemically connected to each other by synapses. A given neuron can be connected to hundreds of thousands of synapses. Each neuron sends and receives electrochemical signals called action potentials to its conne ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Statistical Inference
Statistical inference is the process of using data analysis to infer properties of an underlying probability distribution.Upton, G., Cook, I. (2008) ''Oxford Dictionary of Statistics'', OUP. . Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population. In machine learning, the term ''inference'' is sometimes used instead to mean "make a prediction, by evaluating an already trained model"; in this context inferring properties of the model is referred to as ''training'' or ''learning'' (rather than ''inference''), and using a model for prediction is referred to as ''inference'' (instead of ''prediction''); se ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Gaussian Noise
Carl Friedrich Gauss (1777–1855) is the eponym of all of the topics listed below. There are over 100 topics all named after this German mathematician and scientist, all in the fields of mathematics, physics, and astronomy. The English eponymous adjective ''Gaussian'' is pronounced . Mathematics Algebra and linear algebra Geometry and differential geometry Number theory Cyclotomic fields *Gaussian period *Gaussian rational *Gauss sum, an exponential sum over Dirichlet characters **Elliptic Gauss sum, an analog of a Gauss sum **Quadratic Gauss sum Analysis, numerical analysis, vector calculus and calculus of variations Complex analysis and convex analysis *Gauss–Lucas theorem *Gauss's continued fraction, an analytic continued fraction derived from the hypergeometric functions *Gauss's test, Gauss's criterion – described oEncyclopedia of Mathematics*Gauss's hypergeometric theorem, an identity on hypergeometric series *Gauss plane Statistics *Gaus ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Declarative Memory
Explicit memory (or declarative memory) is one of the two main types of Long-term memory, long-term human memory, the other of which is implicit memory. Explicit memory is the Consciousness, conscious, intentional Recall (memory), recollection of factual information, previous experiences, and concepts. This type of memory is dependent upon three processes: acquisition, Memory Consolidation, consolidation, and retrieval. Explicit memory can be divided into two categories: episodic memory, which stores specific Experience, personal experiences, and semantic memory, which stores factual information.Tulving E. 1972. Episodic and semantic memory. In Organization of Memory, ed. E Tulving, W Donaldson, pp. 381–403. New York: Academic Explicit memory requires gradual learning, with multiple presentations of a Stimulus (psychology), stimulus and response. The type of knowledge that is stored in explicit memory is called declarative knowledge. Its counterpart, known as implicit memory, re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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ACT-R
ACT-R (pronounced /ˌækt ˈɑr/; short for "Adaptive Control of Thought—Rational") is a cognitive architecture mainly developed by John Robert Anderson and Christian Lebiere at Carnegie Mellon University. Like any cognitive architecture, ACT-R aims to define the basic and irreducible cognitive and perceptual operations that enable the human mind. In theory, each task that humans can perform should consist of a series of these discrete operations. Most of the ACT-R's basic assumptions are also inspired by the progress of cognitive neuroscience, and ACT-R can be seen and described as a way of specifying how the brain itself is organized in a way that enables individual processing modules to produce cognition. Inspiration ACT-R has been inspired by the work of Allen Newell, and especially by his lifelong championing the idea of unified theories as the only way to truly uncover the underpinnings of cognition. In fact, Anderson usually credits Newell as the major source of infl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Matrix (mathematics)
In mathematics, a matrix (: matrices) is a rectangle, rectangular array or table of numbers, symbol (formal), symbols, or expression (mathematics), expressions, with elements or entries arranged in rows and columns, which is used to represent a mathematical object or property of such an object. For example, \begin1 & 9 & -13 \\20 & 5 & -6 \end is a matrix with two rows and three columns. This is often referred to as a "two-by-three matrix", a " matrix", or a matrix of dimension . Matrices are commonly used in linear algebra, where they represent linear maps. In geometry, matrices are widely used for specifying and representing geometric transformations (for example rotation (mathematics), rotations) and coordinate changes. In numerical analysis, many computational problems are solved by reducing them to a matrix computation, and this often involves computing with matrices of huge dimensions. Matrices are used in most areas of mathematics and scientific fields, either directly ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Semantic Relatedness
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of language, concepts or instances, through a numerical description obtained according to the comparison of information supporting their meaning or describing their nature. The term semantic similarity is often confused with semantic relatedness. Semantic relatedness includes any relation between two terms, while semantic similarity only includes "is a" relations. For example, "car" is similar to "bus", but is also related to "road" and "driving". Computationally, semantic similarity can be estimated by defining a topological similarity, by using ontologies to define the distance between terms/concepts. For example, a naive metric for the comparison of concepts or ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Hebbian
Hebbian theory is a neuropsychological theory claiming that an increase in synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity, the adaptation of neurons during the learning process. Hebbian theory was introduced by Donald Hebb in his 1949 book '' The Organization of Behavior.'' The theory is also called Hebb's rule, Hebb's postulate, and cell assembly theory. Hebb states it as follows: Let us assume that the persistence or repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add to its stability. ... When an axon of cell ''A'' is near enough to excite a cell ''B'' and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that ''A''’s efficiency, as one of the cells firing ''B'', is increased. The theory is often summarized as "Neurons that fire togethe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Association (psychology)
Association in psychology refers to a mental connection between concepts, events, or mental states that usually stems from specific experiences.Klein, Stephen (2012). ''Learning: Principles and Applications'' (6 ed.). SAGE Publications. . Associations are seen throughout several schools of thought in psychology including behaviorism, associationism, psychoanalysis, social psychology, and structuralism. The idea stems from Plato and Aristotle, especially with regard to the succession of memories, and it was carried on by philosophers such as John Locke, David Hume, David Hartley (philosopher), David Hartley, and James Mill.Boring, E. G. (1950). It finds its place in modern psychology in such areas as memory, learning, and the study of neural pathways. Learned associations Associative learning is when a subject creates a relationship between stimuli (e.g. auditory or visual) or behavior and the original stimulus. The higher the concreteness of stimulus items, the more likely ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Semantic Feature-comparison Model
The semantic feature comparison model is used "to derive predictions about categorization times in a situation where a subject must rapidly decide whether a test item is a member of a particular target category".Smith, E. E., Shoben. E. J., and Rips, L. J. (1974). Structure and Process in Semantic Memory: A Feature Model for Semantic Decisions. Psychological Review, 81(3), 214–241. In this semantic model, there is an assumption that certain occurrences are categorized using its features or attributes of the two subjects that represent the part and the group. A statement often used to explain this model is "a robin is a bird". The meaning of the words ''robin'' and ''bird'' are stored in the memory by virtue of a list of features which can be used to ultimately define their categories, although the extent of their association with a particular category varies. History This model was conceptualized by Edward Smith, Edward Shoben and Lance Rips in 1974 after they derived various ob ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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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] |