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Case-based Reasoning
Case-based reasoning (CBR), broadly construed, is the process of solving new problems based on the solutions of similar past problems. In everyday life, an auto mechanic who fixes an engine by recalling another car that exhibited similar symptoms is using case-based reasoning. A lawyer who advocates a particular outcome in a trial based on legal precedents or a judge who creates case law is using case-based reasoning. So, too, an engineer copying working elements of nature (practicing biomimicry) is treating nature as a database of solutions to problems. Case-based reasoning is a prominent type of analogy solution making. It has been argued that case-based reasoning is not only a powerful method for computer reasoning, but also a pervasive behavior in everyday human problem solving; or, more radically, that all reasoning is based on past cases personally experienced. This view is related to prototype theory, which is most deeply explored in cognitive science. Process Case ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mechanic
A mechanic is a skilled tradesperson who uses tools to build, maintain, or repair machinery, especially engines. Formerly, the term meant any member of the handicraft trades, but by the early 20th century, it had come to mean one who works with machinery. Duties Most mechanics specialize in a particular field, such as auto body mechanics, diesel mechanics, air conditioning and refrigeration mechanics, auto mechanics, bicycle mechanics, boiler mechanics, race car mechanics, aircraft mechanics, and other areas. There are also mobile mechanics who work on heavy equipment that will come to you if there is an issue that must be resolved at the location of the machine. A mechanic is typically certified by a trade association or regional government power. Mechanics may be separated into two classes based on the type of machines they work on, heavyweight and lightweight. Heavyweight work is on larger machines or heavy equipment, such as tractors, construction equipment, and trai ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rule Induction
Rule induction is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a full scientific model of the data, or merely represent local patterns in the data. Data mining in general and rule induction in detail are trying to create algorithms without human programming but with analyzing existing data structures. In the easiest case, a rule is expressed with “if-then statements” and was created with the ID3 algorithm for decision tree learning. Rule learning algorithm are taking training data as input and creating rules by partitioning the table with cluster analysis. A possible alternative over the ID3 algorithm is genetic programming which evolves a program until it fits to the data. Creating different algorithm and testing them with input data can be realized in the WEKA software. Additional tools are machine learning libraries for Python, like scikit-learn. Paradigms Some major rule induction para ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Duck Test
The duck test is a frequently cited colloquial example of abductive reasoning. Its usual expression is: The test implies that a person can identify an unknown subject by observing that subject's habitual characteristics. It is sometimes used to counter abstraction, abstract arguments that something might not be what it appears to be. Notable uses Indiana poet James Whitcomb Riley (1849–1916) may have coined the phrase when he wrote: A common variation of the wording of the phrase may have originated much later with Emil Mazey, secretary-treasurer of the United Auto Workers, at a labor meeting in 1946 accusing a person of being a communist: The term was later popularized in the United States by Richard Cunningham Patterson Jr., Ambassadors from the United States, United States ambassador to Guatemala in 1950 during the Cold War, who used the phrase when he accused Guatemala's Jacobo Arbenz Guzmán government of being Communist. Patterson explained his reasoning as fol ... [...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] |
Artificial Intelligence Detection Software
Artificial intelligence detection software aims to determine whether some content (text, image, video or audio) was generated using artificial intelligence (AI). However, this software is often unreliable. Accuracy issues Many AI detection tools have been shown to be unreliable when generating AI-generated text. In a 2023 study conducted by Weber-Wulff et al., researchers evaluated 14 detection tools including Turnitin and GPTZero and found that "all scored below 80% of accuracy and only 5 over 70%." They also found that these tools tend to have a bias for classifying texts more as human than as AI, and that accuracy of these tools worsens upon paraphrasing. False positives In AI content detection, a false positive is when human-written work is incorrectly flagged as AI-written. Many AI detection platforms claim to have a minimal level of false positives, with Turnitin claiming a less than 1% false positive rate. However, later research by The Washington Post produced much ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AI Alignment
In the field of artificial intelligence (AI), alignment aims to steer AI systems toward a person's or group's intended goals, preferences, or ethical principles. An AI system is considered ''aligned'' if it advances the intended objectives. A ''misaligned'' AI system pursues unintended objectives. It is often challenging for AI designers to align an AI system because it is difficult for them to specify the full range of desired and undesired behaviors. Therefore, AI designers often use simpler ''proxy goals'', such as Reinforcement learning from human feedback, gaining human approval. But proxy goals can overlook necessary constraints or reward the AI system for merely ''appearing'' aligned. AI systems may also find loopholes that allow them to accomplish their proxy goals efficiently but in unintended, sometimes harmful, ways (reward hacking). Advanced AI systems may develop unwanted Instrumental convergence, instrumental strategies, such as seeking power or survival because s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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] |
Janet Kolodner
Janet Lynne Kolodner is an American cognitive scientist and learning scientist. She is a Professor of the Practice at the Lynch School of Education at Boston College and co-lead of the MA Program in Learning Engineering. She is also Regents' Professor Emerita in the School of Interactive Computing, College of Computing at the Georgia Institute of Technology. She was Founding Editor in Chief of '' The Journal of the Learning Sciences'' and served in that role for 19 years. She was Founding Executive Officer of the International Society of the Learning Sciences (ISLS). From August, 2010 through July, 2014, she was a program officer at the National Science Foundation and headed up the Cyberlearning and Future Learning Technologies program (originally called Cyberlearning: Transforming Education). Since finishing at NSF, she is working toward a set of projects that will integrate learning technologies coherently to support disciplinary and everyday learning, support project-based p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Yale University
Yale University is a Private university, private Ivy League research university in New Haven, Connecticut, United States. Founded in 1701, Yale is the List of Colonial Colleges, third-oldest institution of higher education in the United States, and one of the nine colonial colleges chartered before the American Revolution. Yale was established as the Collegiate School in 1701 by Congregationalism in the United States, Congregationalist clergy of the Connecticut Colony. Originally restricted to instructing ministers in theology and sacred languages, the school's curriculum expanded, incorporating humanities and sciences by the time of the American Revolution. In the 19th century, the college expanded into graduate and professional instruction, awarding the first Doctor of Philosophy, PhD in the United States in 1861 and organizing as a university in 1887. Yale's faculty and student populations grew rapidly after 1890 due to the expansion of the physical campus and its scientif ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Roger Schank
Roger Carl Schank (March 12, 1946 – January 29, 2023) was an American artificial intelligence theorist, cognitive psychologist, learning scientist, educational reformer, and entrepreneur. Beginning in the late 1960s, he pioneered conceptual dependency theory (within the context of natural language understanding) and case-based reasoning, both of which challenged cognitivist views of memory and reasoning. He began his career teaching at Yale University and Stanford University. In 1989, Schank was granted $30 million in a ten-year commitment to his research and development by Andersen Consulting, through which he founded the Institute for the Learning Sciences (ILS) at Northwestern University in Chicago. Early life Schank was born in Manhattan, New York, in 1946, and he attended Stuyvesant High School. Academic career For his undergraduate degree, Schank studied mathematics at Carnegie Mellon University in Pittsburgh PA, and later was awarded a PhD in linguistics at the Univ ... [...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] |
Anecdotal Evidence
Anecdotal evidence (or anecdata) is evidence based on descriptions and reports of individual, personal experiences, or observations, collected in a non- systematic manner. The term ''anecdotal'' encompasses a variety of forms of evidence. This word refers to personal experiences, self-reported claims, or eyewitness accounts of others, including those from fictional sources, making it a broad category that can lead to confusion due to its varied interpretations. Anecdotal evidence can be true or false but is not usually subjected to the methodology of scholarly method, the scientific method, or the rules of legal, historical, academic, or intellectual rigor, meaning that there are little or no safeguards against fabrication or inaccuracy. However, the use of anecdotal reports in advertising or promotion of a product, service, or idea may be considered a testimonial, which is highly regulated in certain jurisdictions. The persuasiveness of anecdotal evidence compared to that of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
