Pacman项目是加州大学伯克利分校提供的一个可视化的AI学习平台.其主体利用python完成.该项目提供了丰富的说明文档,以及预先实现了一些简单的算法供参考各接口的使用. http://ai.berkeley.edu/project_overview.html 本文利用Pac-Man平台实现简单的对抗搜索. Part1 : Reflex Agent 提供的ReflexAgent有以下接口: class ReflexAgent(Agent): def getAction(self,gameSta

# sudo pacman -Syu...error: key "5F702428F70E0903" could not be looked up remotelyerror: required key missing from keyringerror: failed to commit transaction (unexpected error)Errors occurred, no packages were upgraded....#sudo pacman -S archlin

Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) ADDITIONAL PRACTICE FOR THE FINAL PROBLEM 1 A box contains 8 dark chocolates, 8 milk chocolates, and 8 white chocolates. (It’s amazing how t

Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Zeros and Ones: Sum of a sample with replacement $S$ is the number of successes: $n$ independent trials, chance of success on a sing

Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Standard Error The standard error of a random variable $X$ is defined by $$SE(X)=\sqrt{E((X-E(X))^2)}$$ $SE$ measures the rough size

Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Law of Large Numbers As the number of trials increases, the chance that the proportion of successes is in the range $$p\pm\text{a fi

Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) PRACTICE PROBLEMS FOR THE MIDTERM PROBLEM 1 In a group of 5 high school students, 2 are in 9th grade, 2 are in 10th grade, and 1 is in 12th

Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Independent $$P(A\cap B)=P(A)\cdot P(B)$$ Binomial Distribution $$C_{n}^{k}\cdot p^k\cdot(1-p)^{n-k}$$ R function: dbinom(k, n, p) U

Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Bayes Theorem $$P(A_i|B)=\frac{P(B|A_i)\cdot P(A_i)}{\sum_{j}P(B|A_j)\cdot P(A_j)}$$ where $$P(B)=\sum_{j}P(B|A_j)\cdot P(A_j)$$ GRA

Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) ADDITIONAL PRACTICE FOR THE FINAL In the following problems you will be asked to choose one of the four options (A)-(D). The options are sta

Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Chi-square test Random sample or not / Good or bad $$H_0: \text{Good model}$$ $$H_A: \text{Not good model}$$ Based on the expected p

Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Dependent Variables (paired samples) SD of the difference is $$\sqrt{\sigma_x^2+\sigma_y^2-2\cdot r\cdot\sigma_x\cdot\sigma_y}$$ whe

Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary One-sample $t$ test Test for a population mean (unknown SD); sample size $n$. That is, known sample mean and SD but unknown populati

Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Test of Hypotheses $$\text{Null}: H_0$$ $$\text{Alternative}: H_A$$ Assuming the null is true, the chance of getting data like the d

Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Academia.edu) Summary Estimating population means and percents Sampling assumptions: Simple Random Sample (SRS) Large enough so that the probability histo

yaourt: 一个pacman前端 本文翻译自:https://archlinux.fr/yaourt-en 1 juin 2007 - admin 关于 简介 获取 示例 截图 链接 关于 Yaourt是一个命令行接口程序,用于在Archlinux上,协同pacman完成软件安装. Written by Julien Mischkowitz <wain at archlinux.fr> and Tuxce <tuxce.net at gmail.com>. 简介 AUR 支持

今天滚系统,再次遭遇包冲突: (/) checking % error: failed to commit transaction (conflicting files) python2-requests: /usr/lib/python2./site-packages/requests/__init__.py exists in filesystem python2-requests: /usr/lib/python2./site-packages/requests/__init__.pyc

libpcap支持一种功能非常强大的过滤语言——“伯克利包过滤”语法.使用BPF过滤规则,你可以确定该获取和检查哪些流量,忽略哪些流量.BPF让你能够通过比较第2.3.4层协议中各个数据字段值的方法对流量进行过滤.BPF中内置了一些“基元”来指代一些常用的协议字段.可以用“host”."prot"之类的基元写出非常简洁的BPF过滤规则,也可以检测位于指定偏移量上的字段(甚至可以是一个位)的值.BPF过滤器也可以由详尽的条件链和嵌套的逻辑“与”.“或”操作组成. BPF基元 现在,构造一

pacman -S package_name #安装软件包pacman -R package_name #删除软件包 pacman -Rs package_name #顺便删除软件包相关依赖pacman -Syu #升级系统中的所有包pacman -Ss package #查询软件包pacman -Qs package #查询已安装的包pacman -Qi package #显示查找的包的信息pacman -Ql package #显示你要找的包的文件都安装的位置pacman -Sw packa

传送门 Sherlock and MiniMax Authored by darkshadows on May 07 2014 Problem Statement Watson gives Sherlock an array $A_1,A_2\cdots A_N$. He asks him to find an integer $M$ between $P$ and $Q$ (both inclusive), such that,$\min \{|A_i-M|, 1\le i\le N\}$ i