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methods in knowledge gathering - Department of Computer Science
methods in knowledge gathering - Department of Computer Science

... Neural Networks • Semi-transparent techniques, such as Branch & Bound, become difficult for human interpretation with large problems • Transparent techniques, such as Expert Systems, become difficult for human interpretation with very large problems - above 1000 rules, the logic chain becomes huge. ...
Artificial Intelligence - Mathematics and Computer Science
Artificial Intelligence - Mathematics and Computer Science

... 1. no consensus as to what is AI 2. Definitions: a. Minsky – “AI is the science of making machines do things that would require intelligence if done by man.” i. Turing – it does make a difference how a machine is intelligent ii. focus on algorithms and programming techniques b. Hayes – “the study of ...
Understanding New Metaphors
Understanding New Metaphors

... The italicized words in these examples are common English words with many polysemous senses. The theory predicts that the meanings of these words in the UNIX domain will be related to their other polysemous senses by one or more of the known regularities. The system was implemented and tested as a c ...
Recent and Current Artificial Intelligence Research in
Recent and Current Artificial Intelligence Research in

... A significant feature of any natural language is that it can serve as its own meta-language. One can use a natural language to talk about the language itself as well as to give instruction in the use and understanding of the language. Because human beings are able to use their natural language to ta ...
Introduction to knowledge-based systems
Introduction to knowledge-based systems

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Overview of AI Research History in USSR and Ukraine - HAL
Overview of AI Research History in USSR and Ukraine - HAL

... concluded with construction of the supercomputers based on integrated circuits (microchip) devices that managed millions operations per second. Two of them after update are still in use in anti-missile and anti-airplane defense systems. Every computer was a new step in computer engineering. Every ne ...
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CPS 570 (Artificial Intelligence at Duke): Introduction
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An introduction to artificial intelligence applications in petroleum
An introduction to artificial intelligence applications in petroleum

... of multilateral wells. The reasoning process in this expert system is based on a systematic planning approach for screening and selecting multilateral well candidates, lateral-section completion types, and the junction levels of complexity. In the 6th paper by Lim of Korea Maritime University, an in ...
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16 - MIT Computer Science and Artificial Intelligence Laboratory

... 16.412J/6.834J Intelligent Embedded Systems Description: Algorithms and paradigms for developing embedded systems that are able to operate autonomously for years at a time within harsh and uncertain environments. Focus on systems that demonstrate high levels of deduction and adaptation. Draws upon a ...
CORRECTED Advanced Computing
CORRECTED Advanced Computing

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The 2005 International Florida Artificial Intelligence
The 2005 International Florida Artificial Intelligence

... vast amounts of data and open access to these data as well as to articles describing approaches and techniques in the area of biomedicine. Hunter pointed out a number of AI technologies that bioinfomaticians rely on, including machine learning (hidden Markov models, clustering, support vector machin ...
Eye on the Prize - Stanford Artificial Intelligence Laboratory
Eye on the Prize - Stanford Artificial Intelligence Laboratory

... argued quite persuasively that the best route toward AI’s main goal lies through the development of performance systems. Edward Feigenbaum, for example, has often said that he learns the most when he throws AI techniques against the wall of hard problems to see where they break. It is true that many ...
Lecture 01 Part A – Introduction to AI
Lecture 01 Part A – Introduction to AI

... • Credit card providers, banks, mortgage companies use AI systems to detect fraud and expedite financial transactions.  Configuring Hardware and Software • AI systems configure custom computer, communications, and manufacturing systems, guaranteeing the purchaser maximum efficiency and minimum ...
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... Group Decision Support Systems (GDSS) Executive Information and Support Systems Overview of Applied Artificial Intelligence (AI) and Problem Solving Fundamentals of Expert Systems Building Expert Systems: Process and Tools Fundamentals of Artificial Neural Networks Neural Network Applications ...
Knowledge management systems
Knowledge management systems

... useful information. 2. Explain the relationship between IT, competitive advantage, and profitability. 3. Discuss five major IT applications used by companies today to build competitive advantage. 4. Identify the major hardware and software components of IT and E-Commerce and describe how they have e ...
Natural Language Processing COMPSCI 423/723
Natural Language Processing COMPSCI 423/723

... • Humans are good at remembering and recognizing patterns; computers are good at crunching numbers ...
Computational Discovery of Communicable Knowledge
Computational Discovery of Communicable Knowledge

...  inputs long-term knowledge and initial short-term elements  provides an interpreter that runs the specified program  incorporates tracing facilities to inspect system behavior Such programming languages ease construction and debugging of knowledge-based systems. Thus, ideas from psychology can s ...
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Systems Development: Chapter 10

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Lecture 4 - The University of Texas at Dallas
Lecture 4 - The University of Texas at Dallas

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Int sys 1 - Intelligent Systems
Int sys 1 - Intelligent Systems

... • Parsers, theorem provers, inference engines • Tools – searching, classification, statistical, pattern matching, abstraction, translation • Tools – problem solvers, game playing, modelling, robotic guidance • Technologies – neural networks, knowledge acquisition, expert systems, planning, dialogue ...
ADVANCED KNOWLEDGE MANAGEMENT
ADVANCED KNOWLEDGE MANAGEMENT

... creation of knowledge. By decentralizing or flattening their organization structures, companies aim to increase knowledge sharing with a larger group of individuals. Organization structures can facilitate KM through communities of practice, which is an organic and self-organized group of individuals ...
Management and Artificial Intelligence: Note
Management and Artificial Intelligence: Note

... employee: This scenario aims at analyzing the different solutions that can be provided to improve the newcomer integration in the organization. For the organisation, it is important to make newcomers rapidly operational by providing them with the information they need about their environment, the pe ...
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Agent - inst.eecs.berkeley.edu

... Images from stanfordracing.org, CMU RoboCup, Honda ASIMO sites ...
Lecture 01 Part A - Introduction to AI
Lecture 01 Part A - Introduction to AI

... • Credit card providers, banks, mortgage companies use AI systems to detect fraud and expedite financial transactions.  Configuring Hardware and Software • AI systems configure custom computer, communications, and manufacturing systems, guaranteeing the purchaser maximum efficiency and minimum ...
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Knowledge representation and reasoning

Knowledge representation and reasoning (KR) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets.Examples of knowledge representation formalisms include semantic nets, systems architecture, Frames, Rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers.
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