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The field of evolutionary computation is expanding dramatically,
fueled by the vast investment that reflects the value of applying
its techniques. Culling material from the Handbook of Evolutionary
Computation, Evolutionary Computation 1: Basic Algorithms and
Operators contains up-to-date information on algorithms and
operators used in evolutionary computing. This volume discusses the
basic ideas that underlie the main paradigms of evolutionary
algorithms, evolution strategies, evolutionary programming, and
genetic programming. It is intended to be used by individual
researchers, teachers, and students working and studying in this
expanding field.
The field of evolutionary computation is expanding dramatically,
fueled by the vast investment that reflects the value of applying
its techniques. Culling material from the Handbook of Evolutionary
Computation, Evolutionary Computation 1: Basic Algorithms and
Operators contains up-to-date information on algorithms and
operators used in evolutionary computing. This volume discusses the
basic ideas that underlie the main paradigms of evolutionary
algorithms, evolution strategies, evolutionary programming, and
genetic programming. It is intended to be used by individual
researchers, teachers, and students working and studying in this
expanding field.
What is missing in most curricula - from elementary school all the
way through to university education - is coursework focused on the
development of problem-solving skills. Most students never learn
how to think about solving problems. Besides being a lot of fun, a
puzzle-based learning approach also does a remarkable job of
convincing students that (a) science is useful and interesting, (b)
the basic courses they take are relevant, (c) mathematics is not
that scary (no need to hate it ), and (d) it is worthwhile to stay
in school, get a degree, and move into the real world which is
loaded with interesting problems (problems perceived as real-world
puzzles).
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