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<h1 class="title">Quick Notes on Reinforcement Learning</h1>
<p class="byline">November 21, 2018</p>
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<h2 id="introduction">Introduction</h2>
<h1 class="title">Quick Notes on Reinforcement Learning</h1>
<p class="byline">November 21, 2018</p>
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<h2 id="introduction">Introduction</h2>
<p>In this series of blog posts, I intend to write my notes as I go through Richard S. Sutton’s excellent <em>Reinforcement Learning: An Introduction</em> <a href="#ref-1">(1)</a>.</p>
<p>I will try to formalise the maths behind it a little bit, mainly because I would like to use it as a useful personal reference to the main concepts in RL. I will probably add a few remarks about a possible implementation as I go on.</p>
<h2 id="relationship-between-agent-and-environment">Relationship between agent and environment</h2>
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<li><span id="ref-1"></span>R. S. Sutton and A. G. Barto, Reinforcement learning: an introduction, Second edition. Cambridge, MA: The MIT Press, 2018.</li>
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