Tuesday, December 31, 2019

Evolutionary Computation A Subfield Of Artificial...

section{Evolutionary Computation} Evolutionary Computation is a subfield of Artificial Intelligence. It is very well-known as its effective global search ability. These algorithms are inspired by biological mechanisms of evolution, social interactions and swarm intelligence. There are several distinguished characteristics of EC algorithms such as the use of a population and the ability of avoiding local optima. A common process of EC algorithms is as follows. Initially, the population are randomly scattered the search space. Along with the evolution process, the population moves according to a predefined fitness function. At the end of the evolution, the individual with the best fitness value is selected as the solution. The origins of evolutionary computation can be traced back to 1950s cite{back1997evolutionary}. Since 1970s, the output of EC research has grown exponentially. The majority of current implementations of EC algorithms descend from three major approaches: emph{genetic algorithms}, emph{evolutionary programming} and emph{evolution strategies}. GA was cite{holland1962outline} introduced by Holland. By far the largest applications of this techniques are in the domain of optimization cite{de1992genetic, de1993genetic}. Evolutionary programming, introduced by Fogel cite{fogel1962autonmous}, was originally attempt to create artificial intelligence. Evolutionary strategies as developed by Rechenberg cite{rechenberg1971} and Schwefel cite{Schwefel1975}, wereShow MoreRelatedARTIFICIAL INTELLIGENCE6331 Words   |  26 PagesARTIFICIAL INTELLIGENCE Contents : Abstract : Introduction : History : Concepts : Branches of AI : Artificial Intelligence in fiction : Problems o 7.1 Deduction, reasoning, problem solving o 7.2 Knowledge representation o 7.3 Planning o 7.4 Learning o 7.5 Motion manipulation o 7.6 Perception o 7.7 Social intelligence o 7.8 Creativity o 7.9 General intelligence ï‚ · VIII : Tools o 8.1 Search optimization o 8.2 Logic o 8.3 Probabilistic methods for uncertain reasoning

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