<story><title>Reinforcement Learning – Bandit Problems</title><url>https://oneraynyday.github.io/ml/2018/05/03/Reinforcement-Learning-Bandit/</url></story><parent_chain><item><author>subatomic</author><text>I was heavily into reinforcement learning around the turn of the century, and at the time, &amp;quot;Reinforcement Learning - An introduction&amp;quot; (Barto and Sutton) &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;mitpress.mit.edu&amp;#x2F;books&amp;#x2F;reinforcement-learning&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;mitpress.mit.edu&amp;#x2F;books&amp;#x2F;reinforcement-learning&lt;/a&gt; was an absolute goldmine for me getting started. I think parts of it are online somewhere including all their pseudocode and solutions.&lt;p&gt;&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;mitpress.mit.edu&amp;#x2F;books&amp;#x2F;reinforcement-learning&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;mitpress.mit.edu&amp;#x2F;books&amp;#x2F;reinforcement-learning&lt;/a&gt;</text></item></parent_chain><comment><author>svalorzen</author><text>The complete first edition can be found here: &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;incompleteideas.net&amp;#x2F;book&amp;#x2F;ebook&amp;#x2F;the-book.html&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;incompleteideas.net&amp;#x2F;book&amp;#x2F;ebook&amp;#x2F;the-book.html&lt;/a&gt;&lt;p&gt;If you&amp;#x27;re interested in some well documented C++ implementations of the algorithms shown in the book, feel free to check out &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;Svalorzen&amp;#x2F;AI-Toolbox&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;Svalorzen&amp;#x2F;AI-Toolbox&lt;/a&gt;. I started the project because when I was first reading the book I had no reference implementation to compare the book to, and personally I learn better with practical examples, so maybe it can help you too.</text></comment>
<story><title>Reinforcement Learning – Bandit Problems</title><url>https://oneraynyday.github.io/ml/2018/05/03/Reinforcement-Learning-Bandit/</url></story><parent_chain><item><author>subatomic</author><text>I was heavily into reinforcement learning around the turn of the century, and at the time, &amp;quot;Reinforcement Learning - An introduction&amp;quot; (Barto and Sutton) &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;mitpress.mit.edu&amp;#x2F;books&amp;#x2F;reinforcement-learning&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;mitpress.mit.edu&amp;#x2F;books&amp;#x2F;reinforcement-learning&lt;/a&gt; was an absolute goldmine for me getting started. I think parts of it are online somewhere including all their pseudocode and solutions.&lt;p&gt;&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;mitpress.mit.edu&amp;#x2F;books&amp;#x2F;reinforcement-learning&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;mitpress.mit.edu&amp;#x2F;books&amp;#x2F;reinforcement-learning&lt;/a&gt;</text></item></parent_chain><comment><author>johnmoberg</author><text>It&amp;#x27;s a fantastic book! The authors have been working on a second edition for a few years, and I think it&amp;#x27;s finally finished. A draft is generously available here: &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;incompleteideas.net&amp;#x2F;book&amp;#x2F;the-book-2nd.html&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;incompleteideas.net&amp;#x2F;book&amp;#x2F;the-book-2nd.html&lt;/a&gt;</text></comment>