求将一段中文摘要翻译成英文

Question

摘要内容是：使用自适应遗传算法对五子棋博弈算法中的评估函数参数进行训练优化.引入陪练算法对训练进行指导,并给出了一种新的适应度函数计算方法,该方法避免了在训练过程中种群个体之间的大量竞赛,从而节省了训练时间.实验表明,训练得到的参数组成的评估函数优于陪练算法中的评估函数.

翻译的好额外给分！
使用软件翻译将不给分。自适应遗传算法应该是adaptive genetic algorithm.

Answer 1

The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function. The use of genetic algorithms for adaptive algorithm backgammon game in the assessment of the function parameters to optimize the training. Algorithm for the introduction of sparring training guide, and gives a new fitness function calculation method to avoid a course of training in population Between a large number of individual competition, thus saving time for training. Experiments show that the training has been formed to assess the parameters of the function algorithm is better than sparring in the assessment of the function.

Answer 2

本人长期从事编辑出版工作，摘要的翻译和校对是日常工作。此摘要，我做了被动态处理，是英文摘要的常规处理方法，希望并应该得到认可。
The parameters of eveluation function in the Gobang Game Algorithm are training optimized using Adaptive Genetic Algorithm.The Tutorial Algorithm is intruduced to guide the training, and a novel calculation method for adaptability function is given. This method can avoid large amount of competitions among populations and individuals during the training process, so that the training time can be reduced. The experiment shows that the evaluation functions composed of the parameters obtained from training are better than those in the Tutorial Algorithm本回答被提问者采纳

Answer 3

我是硕士，翻译了半个小时，语法和内容绝对正确！！！请参考！！Uses the auto-adapted genetic algorithm to gamble in the algorithm for the gobang the appraisal function parameter to carry on the training optimization. The introduction plays as the opponent in order to give others practice the algorithm to train carries on the instruction, and has given one new sufficiency functional calculus method, this method has avoided in the training process between the population individual massive competitions, thus has saved the training time. The experiment indicated that the training obtains the parameter composition's appraisal function surpasses plays as the opponent in order to give others practice in the algorithm appraisal function.

Answer 4

你用金山快译这个软件就可以.翻译如下:Use certainly fit in with inheritance algorithm to carry out the optimization training on the parameter appraising a function in five son board game game algorithm. Have led into the ladder player algorithm guiding to the go along training , have given one kind of new fit in with function out and reckoning, population is particular in that method having been avoided in the process training between large amount of contest, has economized training time thereby. The algorithm the experiment being indicated , training the ladder player better than appraising a function that the parameter is composed of hits the target appraising a function.

Answer 5

The content of this abstract is:

尽量按汉语的句子，用尽量少的句子来表述吧：

To practice and optimize the evaluation function parameter in gobang game playing algorithm with adaptive genetic algorithm, introducing partner training arithmetic for guiding the practice and providing the new fitness function which can avoid massive competition among groups and individuals. Then it will save the practice time. Experiments showed that evaluation function from parameters getting from practices is superior to evaluation function in partner training arithmetic.