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Decision-Theoretic Planning for Intelligent User Interfaces
Decision-Theoretic Planning for Intelligent User Interfaces

... The course of interaction between a system and a user cannot in general be predicted with certainty. An interface that is able to anticipate the user’s actions several steps ahead can better adapt to the situation at hand, steer the interaction in a promising direction, and protect the user from pos ...
Artificial Neural Networks - Computer Science, Stony Brook University
Artificial Neural Networks - Computer Science, Stony Brook University

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A physics approach to classical and quantum machine learning
A physics approach to classical and quantum machine learning

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MEDICAL DIAGNOSIS BY INTERACTING NEURAL AGENTS
MEDICAL DIAGNOSIS BY INTERACTING NEURAL AGENTS

... To design and implement systems that include both hierarchical organizational structures as well as decentralized control Arthur Koestler proposed the holonic paradigm (cf. [24]). The underlying concept is the holon, which describes a basic unit of an organization in social and biological systems. H ...
BNAIC05.pdf
BNAIC05.pdf

... The classical entailment in logics is explosive: any formula is a logical consequence of a contradiction. Therefore, conclusions drawn from an inconsistent knowledge base by classical inference may be completely meaningless. The general task of an inconsistency reasoner is: given an inconsistent ont ...
original
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...  More on This Topic: Machine Learning and Pattern Recognition (CIS732)  Next: How to Find This Hypothesis? CIS 530 / 730: Artificial Intelligence ...
AAAI Spring Symposium, Stanford, March 27
AAAI Spring Symposium, Stanford, March 27

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MACHINE LEARNING WHAT IS MACHINE LEARNING?

... supporting argument to this issue. First of all, implanting learning ability in computers is practically necessary. Present day computer applications require the representation of huge amount of complex knowledge and data in programs and thus require tremendous amount of work. Our ability to code th ...
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PowerPoint Presentation - Computing Science

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Natural language processing Prof. Pushpak Bhattacharyya
Natural language processing Prof. Pushpak Bhattacharyya

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Notes on the IBM Watson Computer System, used on
Notes on the IBM Watson Computer System, used on

... think… machines with minds, in the full and literal sense.” (Haugeland, 1985) “[The automation of] activities that we associate with human thinking, activities such as decision-making, Richard Bellman (1920-84) problem solving, learning…” (Bellman, 1978) ...
papers - CiteSeerX
papers - CiteSeerX

... the range of problems that can be tackled by automated fusion systems. However, for problems of the scale required for maritime predictive analysis, exact evidential reasoning is generally intractable. Traditional fusion systems cope with complexity by decomposing the problem into hypothesis managem ...
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PDF

... well as mixed initiative frameworks, which allow the human expertise to be in the loop. The challenge lies in providing representations that are expressive enough to describe realworld problems and at the same time guaranteeing good and fast solutions. Problem structure, duality, and randomization a ...
Notes on the IBM Watson Computer System, used on
Notes on the IBM Watson Computer System, used on

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image.ntua.gr
image.ntua.gr

... ECG Analysis Module ECG is a complex signal and there are several time-templates for which medical experts are searching for in order to provide their diagnosis. Figure 1 shows a typical ECG waveform. The basic characteristics of the ECG that medical experts examine are related with the form of the ...
MS PowerPoint 97/2000 format
MS PowerPoint 97/2000 format

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a meta-interpreter based on paraconsistent legal knowledge
a meta-interpreter based on paraconsistent legal knowledge

... defining modeling in Legal Knowledge Engineering, divides this area in some approximations, based on: activities such as, litigation or layout of contracts; formalism, through logical adaptations applied to the juridical area in developed specialist systems, such as in Prolog language, reasoning, wi ...
Recitation Slides - Daniel R. Schlegel
Recitation Slides - Daniel R. Schlegel

... Betty is the Passenger <=> ~Betty is the Driver What are the intensional semantics? Betty is the passenger if and only if Betty is not the driver. What are the extensional semantics? …is true if [[Betty is the Passenger]] and [[~Betty is the driver]] are both true or both false, otherwise it is fals ...
CSC 480: Artificial Intelligence
CSC 480: Artificial Intelligence

... are stored in long-term memory  temporary knowledge is kept in short-term memory  sensory input or thinking triggers the activation of rules  activated rules may trigger further activation  a cognitive processor combines evidence from currently active rules ...
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15. MANAGING KNOWLEDGE

... products, and markets, including competitive intelligence 3. INFORMAL, internal knowledge, often called TACIT KNOWLEDGE, which resides in the minds of individual employees but has not been documented in structured form ...
Bayesian Networks in Reliability: Some Recent Developments
Bayesian Networks in Reliability: Some Recent Developments

... of random variables {X1 , . . . , Xn } by specifying a set of conditional independence statements together with a set of conditional probability functions. More specifically, a BN consists of a qualitative part, a directed acyclic graph where the nodes mirror the random variables Xi , and a quantita ...
Study Questions for Creating Life in the Lab, by Fazale Rana, PhD
Study Questions for Creating Life in the Lab, by Fazale Rana, PhD

... experiment, the more artificial and unrealistic the results become. 6. Why is this involvement beneficial? Only by elaborate design and deliberate manipulation of experimental conditions can scientists tease out the critical mechanistic features of the process under investigation. 7. What is the goa ...
MS PowerPoint format
MS PowerPoint format

... – Given: 1000 training documents (posts) from each group – Return: classifier for new documents that identifies the group it belongs to ...
A proposal of a novel model for Artificial Intelligence Planning
A proposal of a novel model for Artificial Intelligence Planning

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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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