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Titlebook: Innovative Teaching and Learning; Knowledge-Based Para Lakhmi C. Jain (Director) Book 2000 Physica-Verlag Heidelberg 2000 artificial intell

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An Introduction to Innovative Teaching and Learning,es. Secondly, since an aim of education in science and technology is to prepare students for their lives in societies which are increasingly dependent upon technology, reflection upon the nature of science and technology is of great benefit for the design of curricula and learning strategies in knowledge-based intelligent techniques.
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On the Architecture of Intelligent Tutoring Systems and Its Application to a Neural Networks Coursel networks simulators. The description of the architecture is followed by a presentation and analysis of a learning model based on which a new Intelligent Tutoring System architecture using collaborating agents is proposed.
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Book 2000s are expert systems, artificial neural networks, fuzzy systems and evolutionary computing. Expert systems are designed to mimic the performance of biological systems. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing
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,Teaching Knowledge Modeling at the Graduate Level — A Case Study,tional information systems and databases, to modern distributed systems and the Internet. That fact is certainly reflected in curricula of different courses and tutorials on AI offered at universities, conferences, and research & development institutions.
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Teaching Course on Artificial Neural Networks,are then recounted gained from a decade of teaching a graduate-level course on ANNs. Representative public domain and commercial ANN software simulators are covered (some of the former types accompanying ANN textbooks). Particular emphasis is placed on BackPropagation/Multi-Layered Perceptrons using NeuralWare software.
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