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Intuitive Statistics
Intuitive statistics, or folk statistics, refers to the cognitive phenomenon where organisms use data to make generalizations and predictions about the world. This can be a small amount of sample data or training instances, which in turn contribute to inductive inferences about either population-level properties, future data, or both. Inferences can involve revising hypotheses, or beliefs, in light of probabilistic data that inform and motivate future predictions. The informal tendency for cognitive animals to intuitively generate statistical inferences, when formalized with certain axioms of probability theory, constitutes statistics as an academic discipline. Because this capacity can accommodate a broad range of informational domains, the subject matter is similarly broad and overlaps substantially with other cognitive phenomena. Indeed, some have argued that "cognition as an intuitive statistician" is an apt companion metaphor to the computer metaphor of cognition. Others appeal ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inductive Reasoning
Inductive reasoning is a method of reasoning in which a general principle is derived from a body of observations. It consists of making broad generalizations based on specific observations. Inductive reasoning is distinct from ''deductive'' reasoning. If the premises are correct, the conclusion of a deductive argument is ''certain''; in contrast, the truth of the conclusion of an inductive argument is '' probable'', based upon the evidence given. Types The types of inductive reasoning include generalization, prediction, statistical syllogism, argument from analogy, and causal inference. Inductive generalization A generalization (more accurately, an ''inductive generalization'') proceeds from a premise about a sample to a conclusion about the population. The observation obtained from this sample is projected onto the broader population. : The proportion Q of the sample has attribute A. : Therefore, the proportion Q of the population has attribute A. For example, say there ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Inference
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". Introduction to Bayes' rule Formal explanation Bayesian inference derives the posterior probability as a consequence of two antecedents: a prior probability and a "likelihood function" derived from a statistical model for the observed data. Bayesian inference computes the posterior probability according to Bayes' theorem: ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Alison Gopnik
Alison Gopnik (born June 16, 1955) is an American professor of psychology and affiliate professor of philosophy at the University of California, Berkeley. She is known for her work in the areas of cognitive and language development, specializing in the effect of language on thought, the development of a theory of mind, and causal learning. Her writing on psychology and cognitive science has appeared in ''Science'', ''Scientific American'', ''The Times Literary Supplement'', ''The New York Review of Books'', ''The New York Times'', ''New Scientist'', ''Slate'' and others. Her body of work also includes four books and over 100 journal articles. She has frequently appeared on TV and radio including ''The Charlie Rose Show'' and ''The Colbert Report''. ''Slate'' writes of Gopnik, "One of the most prominent researchers in the field, Gopnik is also one of the finest writers, with a special gift for relating scientific research to the questions that parents and others most want answer ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Predictive Coding
In neuroscience, predictive coding (also known as predictive processing) is a theory of brain function which postulates that the brain is constantly generating and updating a "mental model" of the environment. According to the theory, such a mental model is used to predict input signals from the senses that are then compared with the actual input signals from those senses. With the rising popularity of representation learning, the theory is being actively pursued and applied in machine learning and related fields. The phrase 'predictive coding' is also used in several other disciplines such as signal-processing technologies and law in loosely-related or unrelated senses. Origins Theoretical ancestors to predictive coding date back as early as 1860 with Helmholtz's concept of unconscious inference. Unconscious inference refers to the idea that the human brain fills in visual information to make sense of a scene. For example, if something is relatively smaller than another object i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inference Engine
In the field of artificial intelligence, an inference engine is a component of the 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 applies 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. Architecture The logic that an inference engine uses is typically represented as IF-THEN rules. The ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Andy Clark
Andy Clark, (born 1957) is a British philosopher who is Professor of Cognitive Philosophy at the University of Sussex. Prior to this, he was at professor of philosophy and Chair in Logic and Metaphysics at the University of Edinburgh in Scotland, director of the Cognitive Science Program at Indiana University in Bloomington, Indiana and previously taught at Washington University in St. Louis, Missouri. Clark is one of the founding members of the CONTACT collaborative research project whose aim is to investigate the role environment plays in shaping the nature of conscious experience. Clark's papers and books deal with the philosophy of mind and he is considered a leading scholar on the subject of mind extension. He has also written extensively on connectionism, robotics and the role and nature of mental representation. Philosophical work Clark's work explores a number of disparate but interrelated themes. Many of these themes run against established wisdom in cognitive pr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayes' Theorem
In probability theory and statistics, Bayes' theorem (alternatively Bayes' law or Bayes' rule), named after Thomas Bayes, describes the probability of an event, based on prior knowledge of conditions that might be related to the event. For example, if the risk of developing health problems is known to increase with age, Bayes' theorem allows the risk to an individual of a known age to be assessed more accurately (by conditioning it on their age) than simply assuming that the individual is typical of the population as a whole. One of the many applications of Bayes' theorem is Bayesian inference, a particular approach to statistical inference. When applied, the probabilities involved in the theorem may have different probability interpretations. With Bayesian probability interpretation, the theorem expresses how a degree of belief, expressed as a probability, should rationally change to account for the availability of related evidence. Bayesian inference is fundamental to Bayesia ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Probability
Bayesian probability is an Probability interpretations, interpretation of the concept of probability, in which, instead of frequentist probability, frequency or propensity probability, propensity of some phenomenon, probability is interpreted as reasonable expectation representing a state of knowledge or as quantification of a personal belief. The Bayesian interpretation of probability can be seen as an extension of propositional logic that enables reasoning with Hypothesis, hypotheses; that is, with propositions whose truth value, truth or falsity is unknown. In the Bayesian view, a probability is assigned to a hypothesis, whereas under frequentist inference, a hypothesis is typically tested without being assigned a probability. Bayesian probability belongs to the category of evidential probabilities; to evaluate the probability of a hypothesis, the Bayesian probabilist specifies a prior probability. This, in turn, is then updated to a posterior probability in the light of new, re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Evolutionary Psychology
Evolutionary psychology is a theoretical approach in psychology that examines cognition and behavior from a modern evolutionary perspective. It seeks to identify human psychological adaptations with regards to the ancestral problems they evolved to solve. In this framework, psychological traits and mechanisms are either functional products of natural and sexual selection, non-adaptive by-products of other adaptive traits, or noise. Adaptationist thinking about physiological mechanisms, such as the heart, lungs, and the liver, is common in evolutionary biology. Evolutionary psychologists apply the same thinking in psychology, arguing that just as the heart evolved to pump blood, and the liver evolved to detoxify poisons, there is modularity of mind in that different psychological mechanisms evolved to solve different adaptive problems. These evolutionary psychologists argue that much of human behavior is the output of psychological adaptations that evolved to solve recurrent p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
John Tooby
John Tooby (born 1952) is an American anthropologist, who, together with psychologist wife Leda Cosmides, helped pioneer the field of evolutionary psychology. Biography Tooby received his PhD in Biological Anthropology from Harvard University in 1989 and is currently Professor of Anthropology at the University of California, Santa Barbara. In 1992, together with Cosmides and Jerome Barkow, Tooby edited '' The Adapted Mind: Evolutionary Psychology and the Generation of Culture''. Tooby and Cosmides also co-founded and co-direct the UCSB Center for Evolutionary Psychology. Cosmides and Tooby are the joint recipient of the 2020 Jean Nicod Prize. Selected publications Books * Barkow, J., Cosmides, L. & Tooby, J., (Eds.) (1992). ''The adapted mind: Evolutionary psychology and the generation of culture''. New York: Oxford University Press. * Tooby, J. & Cosmides, L. (in press). ''Evolutionary psychology: Foundational papers''. Cambridge, MA: MIT Press. * Cosmides, L. & Tooby, J. (i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Leda Cosmides
Leda Cosmides (born May 1957) is an American psychologist, who, together with anthropologist husband John Tooby, helped develop the field of evolutionary psychology. Biography Cosmides originally studied biology at Radcliffe College/Harvard University, receiving her BA in 1979. While an undergraduate, she was influenced by the renowned evolutionary biologist Robert L. Trivers, who was her advisor. In 1985, Cosmides received a PhD in cognitive psychology from Harvard. After completing postdoctoral work under Roger Shepard at Stanford University, she joined the faculty of the University of California, Santa Barbara in 1991, becoming a full professor in 2000. In 1992, together with Tooby and Jerome Barkow, Cosmides edited '' The Adapted Mind: Evolutionary Psychology and the Generation of Culture''. She and Tooby also co-founded and co-direct the Center for Evolutionary Psychology. Cosmides was awarded the 1988 American Association for the Advancement of Science Prize for Behavi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Frequentist Probability
Frequentist probability or frequentism is an interpretation of probability; it defines an event's probability as the limit of its relative frequency in many trials (the long-run probability). Probabilities can be found (in principle) by a repeatable objective process (and are thus ideally devoid of opinion). The continued use of frequentist methods in scientific inference, however, has been called into question. The development of the frequentist account was motivated by the problems and paradoxes of the previously dominant viewpoint, the classical interpretation. In the classical interpretation, probability was defined in terms of the principle of indifference, based on the natural symmetry of a problem, so, ''e.g.'' the probabilities of dice games arise from the natural symmetric 6-sidedness of the cube. This classical interpretation stumbled at any statistical problem that has no natural symmetry for reasoning. Definition In the frequentist interpretation, probabilities are ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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