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An Overview of Evolutionary Computation

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Abstract

Evolutionary computation uses computational models of evolutionary processes as key elements in the design and implementation of computer-based problem solving systems. In this paper we provide an overview of evolutionary computation, and describe several evolutionary algorithms that are currently of interest. Important similarities and differences are noted, which lead to a discussion of important issues that need to be resolved, and items for future research.
post
match Rule ListMessage List
input
message output
message
Output interface
effectors
Bucket brigade
(adjusts rule strengths)
(generates new rules)
Genetic algorithm
Payoff
Environment
Input interface
detectors
... Evolutionary computation solves problems by mimicking evolution steps in nature [6] [7]. Mimicking a natural process gives some abilities [8][9] to evolutionary computation. ...
... Evolutionary computation is a set of techniques that employ principles of natural evolution, such as reproduction, mutation and selection to solve problems and optimize systems [79]. In the context of video game AI, evolutionary computation can be utilized to enhance the performance and capabilities of AI characters within a game. ...
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... Evolutionary computation methods arose from taking inspiration from biological mechanisms to design and implement computer-based problem-solving systems (Spears et al., 1993). This collection of methods allowed the creation of evolving and adaptive solutions to complex problems, especially the ones that impose challenges to traditional algorithms, such as randomness, chaotic disturbances, and complex non-linear dynamics, as outlined by Fogel (2000). ...
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... Although crossover may be disruptive and split apart a good individual in addition to being helpful in bringing two useful components together, the selection pressure in GAs is often constructive. Since disruption of good solutions is practically guaranteed when they are close to the best solution, mimetic algorithms are frequently utilized for the closing stages of such situations where crossover can be very disruptive [26], [36] and [61]. The offspring will be organically adapted to the environment, much like native species, if crossovers occur and the more successful parents are selected more frequently than the less successful ones. ...
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