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CS 561a: Introduction to Artificial Intelligence
CS 561a: Introduction to Artificial Intelligence

... • AI research has both theoretical and experimental sides. The experimental side has both basic and applied aspects. • There are two main lines of research: • One is biological, based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiology. • ...
Introduction to AI - Dr Shahriar Bijani
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... Both approaches (roughly, Cognitive Science and Cognitive Neuroscience) are now distinct from AI ...
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... and primates. Many insects simply act out genetically determined behaviours, with the species surviving due to sheer number of individuals. The more sophisticated the biological system becomes, the more scope there is for adaptation, learning and error. The more sophisticated the biological system b ...
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Stanford Heuristic Programming Project Memo HPP-78
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... spectrometry to infer constraints. For example, it may infer that the unknown molecule is probably a ketone but definitely not a methylketone. Planning information like this is put on the generator% lists of good and bad structural features. Planning has been limited almost entirely to mass spectrom ...
Principles of Rule-Based Expert Systems
Principles of Rule-Based Expert Systems

... [RebohH], EXPERT peiss79a], and OPS [Forgy77] -- provide considerable help. For example, working prototypes of new expert systems with one or two dozen rules have been constructed in a few days using EMYCIN [BennetGla]. Considerable effort is then required to refine the knowledge base, but the effor ...
Dr. Eick`s Introduction to AI
Dr. Eick`s Introduction to AI

... • Computer can work in environment that are unsuitable for human beings. • If computers control everything --- who controls the computers? • If computers are intelligent what civil rights should be given to computers? • If computers can perform most of our work; what should the human beings do? • On ...
James C. Bezdek Computer Science, U. of Melbourne, Parkville, Vic
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... editors, will introduce the Journal’s publisher and will explain the process through which your papers pass between submission and appearance in print. The current editors conceived of Computational Intelligence during late 1983. We suspected that though artificial intelligence (AI) papers were bein ...
AI Techniques for Personalized Recommendation Tutorial
AI Techniques for Personalized Recommendation Tutorial

... collaborative filtering to case-based reasoning and decision-theoretic approaches. These techniques are discussed in relation to the wide variety of research and commercial applications that employ AI-based recommendation. The algorithms, applications, and interfaces presented will be illustrated th ...
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... between ideas grew more likely-to-be-followed as they became well worn, but since it was not Hume's job, surely, to explain in more detail the mechanics of these links, problems about how such paths could be put to good use - and not just turned into an impenetrable maze of untraversable alternative ...
AAAI News - Association for the Advancement of Artificial Intelligence
AAAI News - Association for the Advancement of Artificial Intelligence

... has provided the core administrative and organizational leadership for AAAI for over nine years. She now plans to expand her skills in conference management to a broader technical community. However, she has agreed to work with the AAAI as a consultant at least until the end of August, 1992. She wil ...
Chapter 12
Chapter 12

... in human experts. • The KBDSS can enhance decisions by supplying tools and enhance computerized DSS. • The foundation of building such systems is the techniques and tools that have been developed in the area of artificial intelligence (AI). 2nd semester 2010 Dr. Qusai Abuein ...
PDF
PDF

The Fourth International Workshop on Nonmonotonic Reasoning
The Fourth International Workshop on Nonmonotonic Reasoning

... with negation as failure, frame-based AI languages, and truth maintenance systems have been cleaned up. In addition, he noted that the importance of a number of formal ideas, including groundedness, causality, and specificity, have been recognized. Vladimir Lifschitz (University of Texas at Austin) ...
Computational Creativity
Computational Creativity

... and emotional content. In an interview (Schwanauer and Levitt, 1993, p. 21), Hiller and Isaacson said that, before addressing the expressiveness issue, simpler problems needed to be handled first. We believe that this was a very correct observation in the fifties. After this seminal work, many other ...
ARTIFICIAL INTELLIGENCE
ARTIFICIAL INTELLIGENCE

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Organizing Data and Information

... own knowledge bases – for instance, they cannot eliminate redundant or contradictory rules. Since they are not generally self-adapting, maintaining an expert system is difficult and labor intensive. Because of the complex relationships represented in the knowledge base, it is sometimes too difficult ...
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Three Alternative Scenarios of Work/Technology 2050 Global Work

Understanding Computers, Chapter 12
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... to help decision makers • Data warehouse (data mart): Comprehensive collection of data about a company and its customers – Often contains information used in BI systems • Data mining: The use of intelligent software to find subtle patterns that may not be otherwise evident – Used in conjunction with ...
IX - AIAI - The University of Edinburgh
IX - AIAI - The University of Edinburgh

... making up a hierarchical description of the process or product. The nodes are related by a set of detailed “Constraints” of various kinds. Finally there can be “Annotations” related to the processes or products, which provide rationale, information and other useful descriptions. The forerunner of
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... components, but ultimately, a developer will need to write these components. Another aspect of overselling is to erroneously assume that agents have somehow solved the problems that have dogged artificial intelligence since its inception. Agent systems typically use AI techniques—in this sense, they ...
Turing Test - University of Windsor
Turing Test - University of Windsor

... What will happen when a rock box is constructed with an electric eye which operates across the opening in the wall so that it releases a rock which descends upon C’s toe whenever C puts his foot through A’s side of the opening, and thus comes to take the part of A in this game? ...
Extending Fuzzy Description Logics with a Possibilistic Layer
Extending Fuzzy Description Logics with a Possibilistic Layer

... Description Logics (DLs for short) are a family of logics for representing structured knowledge which have proved to be very useful as ontology languages. Nevertheless, it has been widely pointed out that classical ontologies are not appropriate to deal with imprecise, vague and uncertain knowledge, ...
a study of intelligent controllers application in distributed systems
a study of intelligent controllers application in distributed systems

... software resources is appropriately handled. There are research attempts to explore the applicability of intelligent control in such different areas of computing like infrastructure provisioning and Distributed Systems. In this paper we study the various Intelligent Controls and discuss the recent t ...
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AI winter

In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The term was coined by analogy to the idea of a nuclear winter. The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later. There were two major winters in 1974–80 and 1987–93 and several smaller episodes, including: 1966: the failure of machine translation, 1970: the abandonment of connectionism, 1971–75: DARPA's frustration with the Speech Understanding Research program at Carnegie Mellon University, 1973: the large decrease in AI research in the United Kingdom in response to the Lighthill report, 1973–74: DARPA's cutbacks to academic AI research in general, 1987: the collapse of the Lisp machine market, 1988: the cancellation of new spending on AI by the Strategic Computing Initiative, 1993: expert systems slowly reaching the bottom, and 1990s: the quiet disappearance of the fifth-generation computer project's original goals.The term first appeared in 1984 as the topic of a public debate at the annual meeting of AAAI (then called the ""American Association of Artificial Intelligence""). It is a chain reaction that begins with pessimism in the AI community, followed by pessimism in the press, followed by a severe cutback in funding, followed by the end of serious research. At the meeting, Roger Schank and Marvin Minsky—two leading AI researchers who had survived the ""winter"" of the 1970s—warned the business community that enthusiasm for AI had spiraled out of control in the '80s and that disappointment would certainly follow. Three years later, the billion-dollar AI industry began to collapse.Hypes are common in many emerging technologies, such as the railway mania or the dot-com bubble. An AI winter is primarily a collapse in the perception of AI by government bureaucrats and venture capitalists. Despite the rise and fall of AI's reputation, it has continued to develop new and successful technologies. AI researcher Rodney Brooks would complain in 2002 that ""there's this stupid myth out there that AI has failed, but AI is around you every second of the day."" In 2005, Ray Kurzweil agreed: ""Many observers still think that the AI winter was the end of the story and that nothing since has come of the AI field. Yet today many thousands of AI applications are deeply embedded in the infrastructure of every industry."" He added: ""the AI winter is long since over.""
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