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extending office systems to manage administrative knowledge
extending office systems to manage administrative knowledge

... as “E,” “A” or “S” to denote “events,” “actions,” or “situations” respectively. Because of the nature of CK, attributes of objects are not given importance, so there are no extensive semantics here. Our philosophy is that there can be a separate and independent mechanism at the implementation level ...
Artificial Intelligent Application to Power System Protection
Artificial Intelligent Application to Power System Protection

... mimicking of intelligence includes not only the ability to make rational decisions, but also to deal with missing data, adapt to existing situations and improve itself in the long time horizon based on the accumulated experience. Three major families of AI techniques are considered to be applied in ...
Legal Aspects of Artificial Intelligence
Legal Aspects of Artificial Intelligence

... Scope and aims of this white paper. This white paper is written from the perspective of the inhouse lawyer reviewing the legal aspects of their organisation’s first AI project. It: • addresses in non-technical terms the question: what is AI? and provides a brief outline of current areas of AI resear ...
MS Word Format - Artificial Intelligence Applications Institute
MS Word Format - Artificial Intelligence Applications Institute

... cal product) which may have parts called sub-nodes 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 ...
1 HYBRID EXPERT SYSTEM OF ROUGH SET AND NEURAL
1 HYBRID EXPERT SYSTEM OF ROUGH SET AND NEURAL

... The rough set approach to neural network can appear by providing a tool for pre-processing for neural network. In this paper a new method for pre-processing data for neural network based on rough set has been developed and merged with neural expert system. The process consists of acquisition of data ...
Probabilistic Reasoning and the Design of Expert Systems
Probabilistic Reasoning and the Design of Expert Systems

... likely that”, “often”, or “sometimes” relations between their conditions and the actions. This is not always the case, of course. The rules in many expert systems express direct cause and effect; for example, in software to configure a computer hardware system there will be no uncertainty as to whet ...
as a PDF
as a PDF

... By conjoining this formula with any formula describing a set of states using variables A, B and C introduced before and querying the BDD engine for the possible instantiations of (A0 , B 0 , C 0 ), we can calculate all states that can be reached by driving the truck to San Francisco in some state fr ...
English
English

... 2015 to 2020, reaching USD 12.5bn by 2020. Afterwards, as AI becomes mainstream, AI’s addressable m ­ arket will significantly accelerate, in our view, reaching revenues in the tens of b ­ illions of US dollars by the end of the next decade, and Asia should be a key revenue ­contributor.  The main ...
A Comparative Study of Soft Computing Methodologies in
A Comparative Study of Soft Computing Methodologies in

... The mapping properties of artificial neural networks have been analyzed by many researchers. Hornik [1], and Funahashi [2] have shown that as long as the hidden layer comprises sufficient number of nonlinear neurons, a function can be realized with a desired degree of accuracy. This proof is followe ...
The DARPA High Performance Knowledge Bases
The DARPA High Performance Knowledge Bases

... scores), but they must be clear and they must be published early in the program. In addition, although performance is important, challenge problems that value performance above all else encourage “one-off” solutions (a solution developed for a specific problem, once only) and discourage researchers ...
A. M. Turing
A. M. Turing

... The different views of the sources of knowledge held by rationalists and empiricists have been accompanied by correspondingly different views of the mind, and it is not hard to see why. If one is an empiricist and so holds, roughly, that there is nothing in the mind that is not first in the senses, ...
Solving Bayesian Networks by Weighted Model Counting
Solving Bayesian Networks by Weighted Model Counting

... 2004) built a system that scales to problems with thousands of variables by combining clause learning, formula-caching, and decomposition into connected components. Model-counting is complete for the complexity class #P, which also includes problems such as computing the permanent of a Boolean matri ...


... proof for the robotics community favors direct demonstrations over simulations for at least two reasons: First, it is difficult to satisfactorily simulate the open world, especially the response of the sensors and emergent properties of multiple behaviors. Second, as the price of commercial research ...
CS 8520: Artificial Intelligence
CS 8520: Artificial Intelligence

... A. Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, many animals and some machines. (John McCarthy, 1956. http://www.formal.Stanford.EDU/jmc/whatisai ) ...
Building a Cultural Intelligence Decision Support System - R
Building a Cultural Intelligence Decision Support System - R

... cultures and the influence that context has on behavior. They know when to suspend judgment and when to look for additional cues. Consequently, they engage in more appropriate behaviors in different intercultural situations. ...
ConceptNet - Media Lab Login
ConceptNet - Media Lab Login

... it knows some things about “getting fired”: People sometimes get fired because they are incompetent. A possible consequence of getting fired is not having money. People need money to pay for food and shelter. Even if the knowledgebase does not have direct affective knowledge about “getting fired,” t ...
Computer-Aided Design and Manufacture
Computer-Aided Design and Manufacture

sloman
sloman

... tiny subset of niche space (even if interesting regions of design space are potentially relevant, as Turing claimed, at least implicitly). For someone interested in designs that fit other regions of niche space, the Turing test would be of limited value: a machine that passed the Turing test with fl ...
The Role of analogy in cognitive science
The Role of analogy in cognitive science

... about relationships and attributes. For humans, analogy is usually quite natural, as our cognitive processes have extensive resources on context, history, and personal experience from which to draw. The real trick is developing a means for such understanding to be automated [2]. To perform computati ...
DUCT: An Upper Confidence Bound Approach to Distributed
DUCT: An Upper Confidence Bound Approach to Distributed

... pruned as soon as their infeasibility is evident, and a search for the next feasible solution is started. Infeasible assignments can easily be recognized by the variable that enforces the infeasible constraint. Thirdly, when a node a does not have an infeasible local problem, but all its children re ...
Artificial Intelligence in Japan
Artificial Intelligence in Japan

... Japanese companies are looking to acquire start-ups in the U.S. but they do not always know what they want to do with the start-up technology. Japan has a weak branding strategy compared with rivals such as IBM which has promoted its AI-based Watson platform for a variety of services. For a long tim ...
Decision Support Systems
Decision Support Systems

... based on estimates of the values of those alternatives. • Supporting a decision means helping people working alone or in a group gather intelligence, generate alternatives and make choices ...
to get the file - Mechanical and Materials Engineering
to get the file - Mechanical and Materials Engineering

... content? It is in the controller just as the intelligence of a human is in the neural connections of the brain. However, it is only possible to see this intelligence through some action just as it would not be possible to see intelligence in a comatose human. Where does the intelligence come from? T ...
Fact Sheet: Bringing Artificial Intelligence to Life
Fact Sheet: Bringing Artificial Intelligence to Life

... Bringing Artificial Intelligence to Life with Intel August 23, 2016 The Path to Artificial Intelligence Artificial Intelligence (AI) may seem like a vision for a distant future, but in truth, AI is all around us as machines are increasingly learning to sense, learn, reason, act and adapt in the real ...
Artificial Neural Networks For Spatial Perception
Artificial Neural Networks For Spatial Perception

... estimation, prediction and learning is needed. Spatial perception, that is the detection and localisation of objects in the scene, has recently been of increased interest in robotics. This localisation is needed for on-line motion planning, obstacle avoidance, and object manipulation. While various ...
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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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