内隐学习的人工神经网络模型

Artificial Neural Network Model about Implicit Learning

近年来，人工神经网络模型常被用来模拟各种心理活动，从而为心理学的一些相关理论提供丰富的证据，内隐学习也不例外。基于权重调整来学习正确反应的人工神经网络模型和内隐学习的两大本质特征间有着极为相应的匹配，因此，人工神经网络模型特别适用于内隐学习研究。到目前为止，针对两种较为普遍的内隐学习任务，已经相应地出现了两种使用较为广泛的神经网络模型——自动联系者和简单循环网络。

These years， Artificial Neural Networks have been used to simulate many kinds of psychological activities， including implicit learning. Neural networks has some traits which are good for simulating implicit learning， such as learning to response correctly through weight adjustment. There are two types of neural network models named autoassociators and simple recurrent networks which are used broadly in cognitive simulation.