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PowerPoint
PowerPoint

... • Natural language is very descriptive, but does not lend itself to efficient processing • Semantic networks and search trees are ...
A Myriad of Automation Serving a Unified Reflective Safe/Moral Will
A Myriad of Automation Serving a Unified Reflective Safe/Moral Will

... when followed by a list of representation schemes, implies and thereby continues to promote a trio of questionable assumptions that we contend have hampered the creation of a truly general artificial intelligence for years. First, it focuses on the specific form of the static product of abstraction, ...
Artifical Intelligence
Artifical Intelligence

... programs that imitate the reasoning processes of experts in solving difficult problems – Human expertise is transferred to the expert system, and users can access the expert system for specific advice – Most expert systems contain information from many human experts and can therefore perform a bette ...
cmps3560_artificial_intelligence
cmps3560_artificial_intelligence

... This course is intended to teach the fundamentals of artificial intelligence which include topics such as expert systems, artificial neural networks, fuzzy logic, inductive learning and evolutionary algorithms. Prerequisite: CMPS 3120 or consent of the instructor. Prerequisite by Topic Programming i ...
Strong Physical Symbol System hypothesis
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...  Imagine An operator in a room, with sets of rules about how to manipulate symbol structures  Slots in wall of room – paper can be passed in, and ...
21/22 January 2008
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... • Define solutions in terms of system-wide variables Computers need not be as complex as biological machines. By incorporating key principles we hope to ...
Industrial and commercial uses of artificial intelligence
Industrial and commercial uses of artificial intelligence

... Bush and Alan Turing (who later for the Turing Award was named after and is equivalent to the “Nobel Prize of Technology”) published papers discussing computer systems on the potential for computers to enhance human thinking and help the mind push the limits of what it could do. Turing would later w ...
Artificial Intelligence in Medicine Harjeev Singh1, Sukhwinder Singh
Artificial Intelligence in Medicine Harjeev Singh1, Sukhwinder Singh

... The earliest work in medical artificial intelligence (AI) dates to the early 1970s, when the field of AI was about 15 years old (the phrase “artificial intelligence” had been first coined at a Dartmouth College conference in 1956 [24]). Early AI in medicine researchers had discovered the relevance o ...
Cognitive Science (BS) - Carnegie Mellon University
Cognitive Science (BS) - Carnegie Mellon University

... The field of cognitive science has grown out of increasingly active interaction among psychology, linguistics, artificial intelligence, philosophy, and neuroscience. All of these fields share the goal of understanding intelligence. By combining these diverse perspectives, students of cognitive scien ...
Lecture 3 Slides
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... Whatever intelligence is, it results from some kind of computation and it’s platform independent. It’s not unique to brains. Symbol manipulation is a type of computation that is sufficient to give rise to intelligent behavior. Any symbol manipulation can be carried out on a Turing machine (and, by t ...
computer games
computer games

... own approach combines parts of all of these camps in a very modern ...
epiphenomenal
epiphenomenal

... Without "understanding" we cannot describe what the machine is doing as "thinking". Because it does not think, it does not have a "mind" in anything like the normal sense of the word. Therefore "strong AI" is mistaken (Searle). ...
Slides - Swarthmore College Department of Computer Science
Slides - Swarthmore College Department of Computer Science

... summarize is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until – in a visible future – the range of problems they can handle will be coextensive with the range to which the human mind ...
DM533 Artificial Intelligence
DM533 Artificial Intelligence

... Alan Turing. “Computational Machinery and Intelligence” Mind (1950) [Reference to machine learning, genetic algorithms, reinforcement learning] Workshop at Dartmouth College in 1956 by John McCarthy, Marvin Minsky, Claude Shannon Allen Newell, Herbert Simon [The field receives the name Artificial In ...
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Advance applications of Artificial Intelligence

... natural use of computers by humans. The data. development of natural languages and speech recognition are major thrusts of this area of AI. In principle, neural networks can compute any Being able to talk to computers and robots in computable function; i.e. they can do everything conversational huma ...
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Intro-1-fall08

... • but how could it understand it? – 1. time passes quickly like an arrow? – 2. command: time the flies the way an arrow times the flies – 3. command: only time those flies which are like an arrow – 4. “time-flies” are fond of arrows • only 1. makes any sense, but how could a computer figure this ...
Artificial Intelligence
Artificial Intelligence

... partial written test C1: half-way through the course C2: at the end of the course. project (P) can be done in collaboration with another person Final grade: 50%C + 50%[C1 or P] ...
Artificial Intelligence in Teaching and Learning
Artificial Intelligence in Teaching and Learning

... Many colleges and universities have seen a steep rise in the number of students pursuing interdisciplinary degrees. Increasingly, students seek degrees in, for example, mechanical engineering with a concentration in anthropology, or U.S. history with a minor in biology, or a double major of mathemat ...
Philosophical issues of artificial intelligence
Philosophical issues of artificial intelligence

... Can a machine be intelligent? Can a machine act intelligently? Can a machine think? Instead of asking these difficult questions we should probably ask whether machines can pass a behavioral intelligence test (Turing). ...
Epistemology and Artificial Intelligence Aaron Sloman
Epistemology and Artificial Intelligence Aaron Sloman

... theories are much too simple to be taken seriously as explanations of human abilities. We don’t yet know how to build sufficiently complex theories. In particular human abilities involve a degree of generality, flexibility and extendability not matched by any present-day expert system. The ability t ...
Revision Lectures - School of Computer Science
Revision Lectures - School of Computer Science

... book chapters won't be expected. (Only expecting the main concepts and overall grasp of main examples.) But of course knowledge of all the above types could be helpful and impressive. ...
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... Sequence ? ...... pick up hard object , Hurl the object to the window Cause hand / foot to move fast and crash into the window Shut the window so hard that the glass breaks ...
Chapter 4 Decision Support and Artificial Intelligence: Brainpower
Chapter 4 Decision Support and Artificial Intelligence: Brainpower

... analyze the opposition’s game  The software breaks down the game day video into plays and player actions  With this information the Patriots can better formulate their strategy ...
Intelligent Systems: Reasoning and Recognition Intelligence
Intelligent Systems: Reasoning and Recognition Intelligence

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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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