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Learning outcomes |
To acquire skills in the main topics of intelligent systems and its application to electric power system and electro-mechatronic systems. This includes the important aspects of artificial intelligence theory, such as fuzzy logic, agents, genetic algorithms, neural networks and machine learning.
Acquisition of skills in the fundamental concepts of intelligent systems, as predicted in the objectives of this curricular unit.
Basic topics such as fuzzy logic, intelligent agents, object-oriented systems, machine learning, genetic algorithms and neural networks should be well understood. as well as some applications to electric power system and electro-mechatronic systems.
Use systems simulation software.
Work individually and within a team.
Develop autonomy and leadership abilities.
Know how to read and write scientific works.
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Main Bibliography |
[1] Laxmidhar Behera; Intelligent Systems and Control Principles and Applications, Oxford University Press, 2010.
[2] Adrian A. Hopgood, Intelligent Systems for Engineers and Scientists, 3rd Edition, CRC Press, 2011.
[3] Alexander M. Meyste, Alex Meystel, James S. Albus, Intelligent Systems: Architecture, Design, and Control, Wiley-Interscience, 2001.
[4] Robert J. Schalkoff, Intelligent Systems: Principles, Paradigms and Pragmatics, Jones & Bartlett Learning, 2009.
[5] Simon Deleonibus, Intelligent Integrated Systems: Devices, Technologies, and Architectures, Pan Stanford Series on Intelligent Nanosystems, Pan Stanford Publishing, 2014.
[6] Ethem Alpaydin, Introduction to Machine Learning, 3rd Edition, The MIT Press, 2014.
[7] Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd Edition, Prentice Hall, 2009.
[8] Christopher M. Bishop, Pattern Recognition and Machine Learning, Information Science and Statistics series, Springer, 2007.
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