介绍感知器学习算法及其变种，给出各种感知器算法的伪代码，指出各种算法的优点。给出感知器算法在线性可分和线性不可分

情况下的误差界定理，讨论各种感知器学习算法的误差界理论，给出各种算法的误差界。介绍感知器学习算法在在线优化场景、强化学习

场景和*机算法中的应用，并对未解决的问题进行讨论。-The perceptron learning algorithm and its variants, pseudo code is given a variety of perceptron algorithm, points out the advantages of various algorithms. Given the perceptron algorithm can be divided and linearly non separable linear

Error bound theorem conditions, discuss various perceptron learning algorithm of error theory, the error bounds are given for various algorithms. The perceptron learning algorithm to optimize the scene, in the online reinforcement learning

Application scenarios and gambling machine algorithm, and discusses the open problems.