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StandEx
说明： 这是书上的代码，C/C++中调用Matlab C Math Library的实现，供大家参考(This is the code book, C/C++ In Matlab C Math Library calls to achieve for your reference)
- 2008-11-25 17:32:44下载
- 积分：1
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periodic_pipe
This programm is main to deal with a periodic flow in the pipe which is part of it
- 2013-07-16 21:14:04下载
- 积分：1
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IES_2009
learning robot implementation
- 2010-01-08 11:07:27下载
- 积分：1
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MAtlab
image polar to convert an image from Matrice to polar conrdinate, its about 5 functions that works toguether
- 2013-12-11 03:25:24下载
- 积分：1
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heat2D_v2
heat 2D code for finite element, very important
- 2013-12-07 00:08:28下载
- 积分：1
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libsvm-3.24
说明： 最新版libsvm安装包和SVM回归预测模型，包含预测数据集(SVM regression prediction model)
- 2021-04-13 22:08:56下载
- 积分：1
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levelnet
水准网平差MATLAB程序，适合于闭合、附和、支导线(MATLAB standard network adjustment procedures, suitable for closure, they endorse, support wires)
- 2008-04-26 18:47:15下载
- 积分：1
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circularMatrix.m
Computes the circulant matrix of a vector.
- 2009-05-16 14:21:37下载
- 积分：1
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Music
阵列麦克风中的music算法，用matlab仿真的(Music algorithm in array microphone, matlab simulation)
- 2012-06-24 20:14:22下载
- 积分：1
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WindyGridWorldQLearning
Q-learning (Watkins, 1989) is a simple way for agents to learn how to act optimally in controlled Markovian
domains. It amounts to an incremental method for dynamic programming which imposes limited computational
demands. It works by successively improving its evaluations of the quality of particular actions at particular states.
This paper presents and proves in detail a convergence theorem for Q,-learning based on that outlined in Watkins
(1989). We show that Q-learning converges to the optimum action-values with probability 1 so long as all actions
are repeatedly sampled in all states and the action-values are represented discretely. We also sketch extensions
to the cases of non-discounted, but absorbing, Markov environments, and where many Q values can be changed
each iteration, rather than just one.
- 2013-04-19 14:23:35下载
- 积分：1
