Computational Intelligence
Papadourakis G.
Computational Intelligence (CI) is a methodology involving computing that exhibits an ability to learn and/or to deal with new situations, such that the system is perceived to possess one or more attributes of reason, such as generalization, discovery, association and abstraction. Silicon-based computational intelligence systems usually comprise hybrids of paradigms such as artificial neural networks, fuzzy systems, and evolutionary algorithms, augmented with knowledge elements, and are often designed to mimic one or more aspects of carbon-based biological intelligence.
The concepts, paradigms, algorithms, and implementation of CI and its constituent methodologies – evolutionary computation, neural networks and fuzzy logic – are the focus of this course. In addition, there is an emphasis on practical applications throughout, that is, how to apply the concepts, paradigms, algorithms, and implementations discussed to practical problems in engineering and computer science.
Computational Intelligence (CI) is a methodology involving computing that exhibits an ability to learn and/or to deal with new situations, such that the system is perceived to possess one or more attributes of reason, such as generalization, discovery, association and abstraction. Silicon-based computational intelligence systems usually comprise hybrids of paradigms such as artificial neural networks, fuzzy systems, and evolutionary algorithms, augmented with knowledge elements, and are often designed to mimic one or more aspects of carbon-based biological intelligence.
The concepts, paradigms, algorithms, and implementation of CI and its constituent methodologies – evolutionary computation, neural networks and fuzzy logic – are the focus of this course. In addition, there is an emphasis on practical applications throughout, that is, how to apply the concepts, paradigms, algorithms, and implementations discussed to practical problems in engineering and computer science.
Computational Intelligence (CI) is a methodology involving computing that exhibits an ability to learn and/or to deal with new situations, such that the system is perceived to possess one or more attributes of reason, such as generalization, discovery, association and abstraction. Silicon-based computational intelligence systems usually comprise hybrids of paradigms such as artificial neural networks, fuzzy systems, and evolutionary algorithms, augmented with knowledge elements, and are often designed to mimic one or more aspects of carbon-based biological intelligence.
The concepts, paradigms, algorithms, and implementation of CI and its constituent methodologies – evolutionary computation, neural networks and fuzzy logic – are the focus of this course. In addition, there is an emphasis on practical applications throughout, that is, how to apply the concepts, paradigms, algorithms, and implementations discussed to practical problems in engineering and computer science.
