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Cognitive Radio Communication and Networking: Principles and Practice by Robert Caiming Qiu, Michael C. Wicks, Zhen Hu, Husheng Li

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Chapter 7

Machine Learning

Artificial intelligence [546–554] aims at making intelligent machines where an intelligent machine or agent is a system that perceives its environment and takes actions to maximize its own utility. The central problems in artificial intelligence include deduction, reasoning [555], problem solving, knowledge representation, learning, and so on.

In order to understand how the brain learns and how the computer or system achieves intelligent behavior, the interdisciplinary study of neuroscience, computer science, cognitive psychology, mathematics, and statistics gives a new research direction of artificial intelligence, called computational neuroscience research. Computational neuroscience tries to build artificial systems and mathematical models to explore the computational principles for perception, cognition, memory, and motion. More related information can be found in Computational Neuroscience Research at Carnegie Mellon University. Leonid Perlovsky, who won the John McLucas Award in 2007, the highest US Air Force Award for science, uses knowledge instinct and dynamic logic to express and model the brain mechanisms of perception and cognition [556]. Especially, dynamic logic is a mathematical description of the knowledge instinct which describes mathematically a fundamental mind mechanism of interactions between bottom-up signals and top-down signals as a process of adaptation from vague to crisp concepts [557]. Besides, bionics also motivates the study ...

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