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ARTIFICIAL INTELLIGENCE IN SOLAR ENERGY APPLICATIONS
ARTIFICIAL INTELLIGENCE IN SOLAR ENERGY APPLICATIONS

... According to Haykin [4] a neural network is a massively parallel distributed processor that has a natural propensity for storing experiential knowledge and making it available for use. It resembles the human brain in two respects; the knowledge is acquired by the network through a learning process, ...
Erich Schweighofer
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... ◦ “Knowledge representation in law is the challenge of how knowledge and information on legal norms, judgements and literature can be represented and how relevant information can be gained for concrete case solutions. This question is at this time above all pursued as special discipline of legal inf ...
Abstract - Artificial Intelligence Applications Institute
Abstract - Artificial Intelligence Applications Institute

... knowledge to users. People assimilate information in different manners, and have distinct limitations and requirements. For instance, deaf or hearing impaired people have different needs related to information acquisition. Therefore, different modalities of visualisation and interaction are needed f ...
A General Reading List for Artificial Intelligence
A General Reading List for Artificial Intelligence

... Supplement the material on semantic nets with the more comprehensive treatment in Nilsson. Production systems are well explained in the Davis and King article that is recommended. Semantic primitives are not a representational formalism per se, but could form the basis of one. For more on this read ...
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... program might never stop looking for it.) The so-called logicist tradition within artificial intelligence hopes to build on such programs to create intelligent systems. There are two main obstacles to this approach. First, it is not easy to take informal knowledge and state it in the formal terms re ...
What is AI? - University at Buffalo, Computer Science and
What is AI? - University at Buffalo, Computer Science and

... terminal of two “entities.” One entity would be a human, the other a machine/computer. “If the judge regularly failed to correctly distinguish the computer from the human, then the computer was said to have passed the test.” * *© István S. N. Berkeley Ph.D. 1997. ...
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... University of Cambridge was in the area of computational linguistics. His subsequent research has covered topics such as machine learning of natural language grammars; analyses of case-based learning; similarity measures, retrieval algorithms, and maintenance algorithms for case-based reasoning; con ...
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... almost four decades ago, the profession has not been able to make use of computers fully, especially, for structural design and planning. This is mainly because of problem specific nature, need for logical reasoning, feasibility constraints and use of past experience required in actual design proces ...
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... – Scan e-mail, documents, and databases to perform knowledge discovery, determine meaningful relationships and rules – Identify patterns in data (usually through neural networks and other data mining techniques) – Forecast future results by using data/knowledge – Provide advice directly from knowled ...
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... • The foundation of building such systems is the techniques and tools that have been developed in the area of artificial intelligence (AI). 2nd semester 2010 Dr. Qusai Abuein ...
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... Cybernetics. Cybernetics is the study of communication in human and machine and it brought together many parallels between human and machine Although the computer provided the technology necessary for AI, it was not until the early 1950’s that the link between human intelligence and machines was rea ...
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... identification and control of dynamical systems-case studies (Inverted Pendulum, Articulation Control) Unit III Fuzzy Systems Classical sets – Fuzzy sets – Fuzzy relations – Fuzzification – Defuzzification – Fuzzy rules Unit IV: Fuzzy Logic Control Membership function – Knowledge base – Decision-mak ...
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Concept mapping and the fundamental problem of moving between

... information. For example, studies that look only at the ʻproportion of correct ideas produced in the concept mapʼ (e.g. Karpicke and Blunt, 2011: 773) fail to acknowledge that some concepts are more important than others in the construction of understanding (Mintzes and Quinn, 2007), or that studen ...
EXPERT SYSTEM - Human Resource Management Academic
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... changes, the program has to be changed and then rebuilt. Knowledge-based systems collect the small fragments of human know-how into a knowledge-base which is used to reason through a problem, using the knowledge that is appropriate. A different problem, within the domain of the knowledgebase, can be ...
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... Minsky on the Vocabulary Problem • “To make our computers easier to use, we must make them more sensitive to our needs. That is, make them understand what we mean when we try to tell them what we want. […] If we want our computers to understand us, we’ll need to equip them with adequate knowledge.” ...
Mtech Syllabus - GEHU CS/IT Deptt
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... Representation-Procedural vs Declarative Knowledge-Predicate logic-representing simple fact – instance and ISA relationships – resolution-natural deduction-Natural Deduction-Structured Representation-Semantic Networks UNIT III KNOWLEDGE ORGANISATION AND MANIPULATION Procedural Vs declaration knowled ...
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How Can Computer Programs Reason?

... flowchart and probabilistic methods we have outlined[8]. Each group noted that despite the ...
artificial intelligence
artificial intelligence

... – Define the term artificial intelligence and state the objective of developing artificial intelligence systems – List the characteristics of intelligent behavior and compare the performance of natural and artificial intelligence systems for each of these characteristics – Identify the major compone ...
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... This theory also has two extensions. This time, however, this does not agree with our intuitions. Amish ...
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... Figure 1 Architecture of a general knowledge support system At the center of Figure 1 is the implementation of knowledge support systems serving specific user communities and each operating through a particular integration system that draws upon the services of the surrounding application sub-system ...
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... • software errors, e.g., coding bugs • “human-like” errors – Clearly, hardware and software errors are possible in practice – what about “human-like” errors? ...
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... Rule Based Expert System Application for Crime against Women Law in Indian judicial system techniques is used to create. „Automated Legal Reasoning Systems.‟ Computer systems that reasons with and apply the law to solve problems. 2.2) Application of Legal Expert System The authors during the study ...
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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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