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The Advantages of Evolutionary Computation
David B. Fogel
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TLDR
Practical advantages of using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence include the flexibility of the procedures, as well as the ability to self-adapt the search for optimum solutions on the fly.Abstract:
Evolutionary computation is becoming common in the solution of difficult, realworld problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific advantages include the flexibility of the procedures, as well as the ability to self-adapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine.read more
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References
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Genetic Algorithms + Data Structures = Evolution Programs
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No free lunch theorems for optimization
TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.
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Artificial Intelligence through Simulated Evolution
TL;DR: This chapter contains sections titled: References Artificial Intelligence through a Simulation of Evolution Natural Automata and Prosthetic Devices and Artificial intelligence through a simulation of Evolution natural automata and prosthetic devices.
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Evolutionary algorithms in theory and practice
TL;DR: In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming within a unified framework, thereby clarifying the similarities and differences of these methods.