Simulating brain functions based on computational learning theory

在本研究中，我们以计算学习理论为基础，建立了运动、思维和记忆等大脑功能模型，并对其行为进行了分析：(1)建立了运动的状态转移模型，并利用该模型模拟了机器人的运动；(2)建立了记忆的神经网络模型，并对其行为进行了分析；(3)利用蒙特卡罗模拟设计了一种高效的纸牌游戏算法。最后，我们基于上述结果构建了一种统一的脑功能模拟方法。

In this study, we construct various models of brain functions, such as motion, thinking and memory based on computational learning theory, and analyze their behavior in the following fashion: (1) we construct a state transition model for the motion and simulate the robot motion using this model, (2) we construct a neural network model for the memory and analyze its behavior, and (3) we design an efficient algorithm for card game playing using Monte Carlo Simulation. Finally we construct a unified methodology for simulating brain functions based on the above results.