kashif

Cross Entropy Method

How do we solve for the policy optimization problem which is to maximize the total reward given some parametrized policy?

Discounted future reward

To begin with, for an episode the total reward is the sum of all the rewards. If our environment is stochastic, we can never be sure if we will get the same rewards the next time we perform the same actions. Thus the more we go into the future the more the total future reward may diverge. So for that reason it is common to use the discounted future reward where the parameter discount is called the discount factor and is between 0 and 1.

A good strategy for an agent would be to always choose an action that maximizes the (discounted) future reward. In other words we want to maximize the expected reward per episode.

rethink-imcmahon

#include "ros/ros.h"
#include "baxter_core_msgs/JointCommand.h"
int main(int argc, char **argv)
{
  ros::init(argc, argv, "baxter_left_arm_joint_pub");
  ros::NodeHandle n;
  ros::Publisher left_cmd_pub = n.advertise<baxter_core_msgs::JointCommand>("/robot/limb/left/joint_command", 1);
  // publish at at least 5 Hz, or else Baxter switches back to Position mode and holds position
  ros::Rate loop_rate(100);
  baxter_core_msgs::JointCommand cmd;

danielgtaylor

Moving to ES6 from CoffeeScript

I fell in love with CoffeeScript a couple of years ago. Javascript has always seemed something of an interesting curiosity to me and I was happy to see the meteoric rise of Node.js, but coming from a background of Python I really preferred a cleaner syntax.

In any fast moving community it is inevitable that things will change, and so today we see a big shift toward ES6, the new version of Javascript. It incorporates a handful of the nicer features from CoffeeScript and is usable today through tools like Babel. Here are some of my thoughts and issues on moving away from CoffeeScript in favor of ES6.

While reading I suggest keeping open a tab to Babel's learning ES6 page. The examples there are great.

Punctuation

Holy punctuation, Batman! Say goodbye to your whitespace and hello to parenthesis, curly braces, and semicolons again. Even with the advanced ES6 syntax you'll find yourself writing a lot more punctuatio

jsdf

// for an updated version see https://github.com/jsdf/react-native-refreshable-listview

var React = require('react-native')
var {
  ListView,
  ActivityIndicatorIOS,
  StyleSheet,
  View,
  Text,
} = React

averyvery

def view_css
  path = "views/#{params[:controller]}/#{params[:action]}"
  stylesheet_link_tag(path) unless Rails.application.assets.find_asset(path).nil?
end

andy-berry-dev

var https = require('https');

var storesUrl = 'https://reserve.cdn-apple.com/GB/en_GB/reserve/iPhone/stores.json';
var stockUrl = 'https://reserve.cdn-apple.com/GB/en_GB/reserve/iPhone/availability.json';

var stockLastUpdated;

var stores;
var stock;

Dmitrii-I

Top 10 algorithms in data mining - with R

Wu et al. describe top 10 algorithms in data mining in (LDO) "Top 10 algorithms in data mining" (2007). How to use these algorithms in R is shown here. The datasets used are available in R itself, no need to download anything. Run data() to see the available datasets. Nothing is original here, everything was Googled, and no references are made to sources. The purpose of all this is to show how quickly you can prototype most algorithms with minimal code, in R.

1. C4.5

require(rJava) # needed for printing strings out of Java objects
require(RWeka) # contains the J48() function that builds C4.5 decision trees 
iris_c4.5 <- J48(Species ~ ., data=iris)
writeLines(rJava::.jstrVal(iris_C4.5$classifier))

basti

# Speed things up by not loading Rails env
config.assets.initialize_on_precompile = false

fenixbrassi

Interactive ruby ready.
> help
> 2 + 6
=> 8
Success!
> 4 * 10
=> 40
> 5 - 12
=> -7
> 40 / 4

rogerleite

Introduction

Some install scripts. Target to work with Ubuntu 12 or greater.

Table of Scripts

• erlang
• logplex
• redis