这种学习规则的基本思想就是：通过不断地优化变异随机选择的连接权矩阵元，从而使网络在给定的训练目标下达到整体最优。
The basic idea of this learning rule is to obtain a certain optimization by continuously changing the elements of coupling matrix selected randomly.
在基本蚁群算法的基础上，用确定性选择与随机性选择相结合的方法对节点的状态转移规则进行改进。
Grid method was applied to establish an environment model. The conversion rule of node state was improved by combining decided selection with random selection.
在基本蚁群算法的基础上，用确定性选择与随机性选择相结合的方法对节点的状态转移规则进行改进。
Grid method was applied to establish an environment model. The conversion rule of node state was improved by combining decided selection with random selection.
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