Innovative Teaching and Learning: Knowledge-Based Paradigms

✍ Scribed by Professor Lakhmi C. Jain (eds.)

• Publisher: Physica-Verlag Heidelberg
• Year: 2000
• Tongue: English
• Leaves: 343
• Series: Studies in Fuzziness and Soft Computing 36
• Edition: 1
• Category: Library

✦ Synopsis

Presented are innovative teaching and learning techniques for the teaching of knowledge-based paradigms. The main knowledge-based intelligent paradigms 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 algorithms are used for optimization applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge.

✦ Table of Contents

Front Matter....Pages i-xii
An Introduction to Innovative Teaching and Learning....Pages 1-30
Teaching and Learning the AI Modeling....Pages 31-86
Artificial Intelligence Techniques for an Interdisciplinary Science Course....Pages 87-104
On the Architecture of Intelligent Tutoring Systems and Its Application to a Neural Networks Course....Pages 105-134
Teaching Knowledge Modeling at the Graduate Level — A Case Study....Pages 135-188
Innovative Modeling Techniques for Intelligent Tutoring Systems....Pages 189-234
Teaching Course on Artificial Neural Networks....Pages 235-260
Innovative Education for Fuzzy Logic Stabilization of Electric Power Systems in a Matlab/Simulink Environment....Pages 261-287
A Neural Network Workbench for Teaching and Learning....Pages 289-309
PRAM: A Courseware System for the Automatic Assessment of AI Programs....Pages 311-329
Back Matter....Pages 331-335

✦ Subjects

Artificial Intelligence (incl. Robotics); Business Information Systems