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Training and Control System for Evolving Solutions to Data-Intensive Problems Using Nested Experience-Layered Individual Pool
Training and Control System for Evolving Solutions to Data-Intensive Problems Using Nested Experience-Layered Individual Pool
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机译:使用嵌套的经验分层个人库来解决数据密集型问题的解决方案的培训和控制系统
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摘要
Roughly described, in an evolutionary technique for finding optimal solutions to a provided problem, a computer system uses a grouping algorithm that is better able to find diverse and optimum solutions in data mining environment with multiple solution landscapes and a plurality of candidate individuals. Each candidate individual identifies with a potential solution, and is associated with a testing experience level and one or more partition tags. Each candidate individual is assigned into one of a plurality of competition groups in dependence upon the individual's testing experience level and partition tag. During competition among candidate individuals, a candidate individual can only replace another candidate individual if both the candidate individuals have a common partition tag and are in the same competition group. A candidate individual cannot replace another candidate individual if they have different partition tags or are in different competition groups.
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