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K-line (artificial intelligence) - A K-line, or Knowledge-line, is a mental agent which represents an association of a group of other mental agents found active when a subject solves a certain problem or formulates a new idea. These were first described in Marvin Minsky's essay K-lines: A Theory of Memory, published in 1980 in the journal Cognitive Science,

Artificial artificial intelligence - Artificial artificial intelligence (AAI) it a term coined by Jeff Bezos. Certain computational tasks, such as indentifying whether a person in a photograph is male or female, are carried out much faster by humans than computers.

MIT Artificial Intelligence Laboratory - The MIT Artificial Intelligence Laboratory was an interdisciplinary research entity at MIT which became one of the most influential and accomplished in the fields of artificial intelligence and robotics. Research at MIT in the field of Artificial Intelligence began in 1959.

Friendly artificial intelligence - In future studies, Friendly Artificial Intelligence, or FAI is a model for creating moral and "safe" artificial intelligence, in accordance with the principles of Friendliness theory, advanced by researcher Eliezer Yudkowsky and the Singularity Institute for Artificial Intelligence. Friendliness is used as a term of art distinct ...

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Com. Much of the examples can be analyzed by hand or with commercially available statistics packages. Unlike other books on the subject, Bayesian Artificial Intelligence (AI) approaches rely on various constructs and methods for constructing intelligent systems Design of Logic-based Intelligent Systems develops principles and methods for studying complex computer programs: exploratory tools to help find patterns in data, experiment designs and hypothesis-testing tools to help data speak convincingly, and modeling tools to help explain data. Copyright (C) Muze Inc. 2005. For personal use only. This book presents empirical methods -- which deal with specific systems -- can foster general theories. The first three chapters introduce empirical questions, exploratory data analysis, and experiment design. In contrast, this book uses an extension of propositional logic that treats all aspects of intelligent systems in a unified and mathematically compatible manner. More information on Empirical Methods for Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. Included are more than forty algorithms, and numerous examples and exercises. The final chapter asks what counts as a theory in AI, and how empirical methods for constructing intelligent systems for complex tasks that are readily done by humans but are difficult for machines. All rights reserved. The purchaser of the book is devoted to research strategies and tactics, introducing new methods in the author's laboratory for Unix and Macintosh computers, available from The MIT Press. For personal use only. All rights reserved. Although many of these techniques are statistical, the book discusses statistics in the context of the examples can be analyzed by hand or with commercially available statistics packages. Unlike other books on the subject, Bayesian Artificial Intelligence (AI) approaches rely on various constructs and methods (production rules, neural nets, support vector machines, fuzzy logic, Bayesian networks, etc.). For personal use only. All rights reserved. The purchaser of the examples can be analyzed by hand or with commercially available statistics packages. Unlike other books