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If intelligence is uncomputable, then…
If intelligence is uncomputable, then…

... And, at that point it might as well stop – since it isn’t allowed to “change its mind”. Suppose that, in dealing with the tape of all ones, it does that after it has seen ten symbols. (It doesn’t matter, for this argument, whether that number is ten or ten million, but ten is easier to visualize.) T ...
Introduction
Introduction

... capabilities of individuals, but on the cooperative behaviour or social interactions of groups • Many species solve problems in groups that could never be solved by any single individual • Examples include ants, termites, bees, many predators, and humans • This has lead to many different types of al ...
For release Tuesday, Dec. 16, at 0600 PST Head Stanford to host
For release Tuesday, Dec. 16, at 0600 PST Head Stanford to host

... of the committee. Together, the seven researchers will form the first AI100 standing committee. It and subsequent committees will identify the most compelling topics in AI at any given time, and convene a panel of experts to study and report on these issues. Horvitz envisions this process repeating ...
Center for Intelligent Technologies - AI-CIT
Center for Intelligent Technologies - AI-CIT

... • Stanislav Kmet - Peter Sincak - Peter Stehlik : Artificial neural network for creep behaviour predictions of a parallel-lay aramid rope under varying stresses, Strain, An International Journal for experimental Mechanics, ISSN: 1475-1305 , CC-indexed , 2010 • Marek Bundzel, Peter Sinčák : Ensemblin ...
Powerpoint
Powerpoint

... When thing (preconditions, constraints, goals,…) need to be stated precisely, logic is often best Example: ...
Artificial Intelligence
Artificial Intelligence

... “Intelligence has been defined in many different ways including one's capacity for logic, understanding, self-awareness, learning, emotional knowledge, planning, creativity and problem solving. It can be more generally described as the ability to perceive information, and retain it as knowledge to b ...
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Artificial Intelligence Overview

... 1. Build systems that think like humans 2. Build systems that act like humans Engineering Approach 1. Build systems that think rationally 2. Build systems that act rationally ...
Artificial Intelligence: Computers do not think
Artificial Intelligence: Computers do not think

... the upper level of mental life of which the person is aware as contrasted with unconscious processes ...
intelligent - Institute for the Study of Learning and Expertise
intelligent - Institute for the Study of Learning and Expertise

...  The Halo project aims to acquire knowledge from scientific textbooks and answer questions in natural language.  The CALO project developed an integrated office assistant that helps with meetings, purchase orders, and other tasks.  The Virtual Human project creates synthetic characters that produ ...
4-up pdf - Computer Sciences User Pages
4-up pdf - Computer Sciences User Pages

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Artificial Intelligence
Artificial Intelligence

... nodes representing concepts (such as MAN and DOG) and labeled links between them (labeled, for example, with OWNS). Frames and semantic networks are thought to be informationally equivalent, which means that there is no loss of information when translating from one to another. Semantic networks are ...
Knowledge management systems - Oman College of Management
Knowledge management systems - Oman College of Management

... Web content management • Web content management focuses on building an effective website framework through which users may access the KMS. ...
IOSR Journal of Computer Engineering (IOSRJCE) ISSN: 2278-0661, ISBN: 2278-8727
IOSR Journal of Computer Engineering (IOSRJCE) ISSN: 2278-0661, ISBN: 2278-8727

... The essence of the Knowledge based approach used in AI, is to ask what knowledge is used by a human expert in solving some task and to develop algorithms and data structures that may represent this knowledge explicitly. Often the most useful facts are a collection of some rules of thumb, derived thr ...
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... lack of standardization in terminology, formats for data logging, measurement scales, not developed, flexible and comfortable for using computer methods of machine representation of medical knowledges, and formalization of the decision making process. Expert systems are one of the most common types ...
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Examination question №13

... 1) Software assistant that performs tasks such as retrieving and delivering information and automating repetitive tasks 2) Text to speech 3) Graphical user interface 4) A project of the Massachusetts Institute of Technology`s Artificial Intelligence ...
INTRODUCTION TO ARTIFICIAL INTELLIGENCE Chapter 1
INTRODUCTION TO ARTIFICIAL INTELLIGENCE Chapter 1

... understand English in a micro-domain (the block world).  1972: PROLOG was developed by a group of Europeans and became alternative to LISP as an AI programming language.  1974: MYCIN was developed by Ted Shortliffe. Expert system for medical diagnosis. Sometimes called the first expert system.  1 ...
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Practical applications of Philosophy in Artificial Intelligence Karim

... assess the validity of the state through a formal proof it will be confused because the statement remains true until the proof is complete. Penrose argues that these types of sentences, which humans can reason about, would be impossible for a computer to understand. What Penrose doesn’t notice is th ...
Materi Pendukung : T0264P06_2 Representation In the 1960s and
Materi Pendukung : T0264P06_2 Representation In the 1960s and

... knowledge base. In this view, inferencing and other interesting information and knowledge processing tasks are not part of natural language processing. By contrast, the computational models of natural language presented in this book view natural language as a knowledge representation and reasoning s ...
Artificial Consciousness: Utopia or Real Possibility?
Artificial Consciousness: Utopia or Real Possibility?

... More recent films, such as James Cameron’s Terminator and the Wachowski brothers’ The Matrix, present an even more catastrophic view of the future in which robots become self-aware and dominate the human race. For example, Cameron’s 1991 film, Terminator 2: Judgment Day, begins with a scene depictin ...
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Perception and behavior (vision, robotic, NLP, bionics …) not

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SELF-REFLECTIVE MACHINE LEARNING
SELF-REFLECTIVE MACHINE LEARNING

experiments in the variety of being - Home page-
experiments in the variety of being - Home page-

... The subject “God” although not dead, e.g. in Christian theology, is taboo in some circles and passé in others; it is something to be avoided. Here are some possible reasons. The discussion focuses on general and academic sentiments c. 2000 in the English speaking world. The first is the idea of sepa ...
Expert Systems - Watford Grammar School for Boys Intranet
Expert Systems - Watford Grammar School for Boys Intranet

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Alan Turing Biography
Alan Turing Biography

... socialize and did not care much about appearance. In school he was known only for being introverted odd, ironic and unwilling to respect rules. At 24, he published an article of great importance to pure mathematics, calling On computable numbers. In it were proved that calculations be made impossibl ...
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History of artificial intelligence

The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with ""an ancient wish to forge the gods.""The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956. Those who attended would become the leaders of AI research for decades. Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation and they were given millions of dollars to make this vision come true. Eventually it became obvious that they had grossly underestimated the difficulty of the project. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned and withdrew funding again. This cycle of boom and bust, of ""AI winters"" and summers, continues to haunt the field. Undaunted, there are those who make extraordinary predictions even now.Progress in AI has continued, despite the rise and fall of its reputation in the eyes of government bureaucrats and venture capitalists. Problems that had begun to seem impossible in 1970 have been solved and the solutions are now used in successful commercial products. However, no machine has been built with a human level of intelligence, contrary to the optimistic predictions of the first generation of AI researchers. ""We can only see a short distance ahead,"" admitted Alan Turing, in a famous 1950 paper that catalyzed the modern search for machines that think. ""But,"" he added, ""we can see much that must be done.""
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