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<oembed><version>1.0</version><provider_name>Glosarix</provider_name><provider_url>https://glosarix.com/en/</provider_url><author_name>Team Glosarix</author_name><author_url>https://glosarix.com/en/author/adm_glosarix/</author_url><title>Reinforcement Learning Exploration - Glosarix</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="zCJw0ITPyw"&gt;&lt;a href="https://glosarix.com/en/glossary/reinforcement-learning-exploration-en/"&gt;Reinforcement Learning Exploration&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/reinforcement-learning-exploration-en/embed/#?secret=zCJw0ITPyw" width="600" height="338" title="&#x201C;Reinforcement Learning Exploration&#x201D; &#x2014; Glosarix" data-secret="zCJw0ITPyw" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Description: Reinforcement Learning Exploration is a fundamental process in the field of machine learning, where an agent interacts with an environment to maximize a reward by testing various actions. This approach is based on the idea that the agent must explore different strategies and actions to discover which are most effective in achieving its goals. [&hellip;]</description></oembed>
