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    <title>PyPI recent updates for envquest</title>
    <link>https://pypi.org/project/envquest/</link>
    <description>Recent updates to the Python Package Index for envquest</description>
    <language>en</language>    <item>
      <title>0.0.12</title>
      <link>https://pypi.org/project/envquest/0.0.12/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Tue, 04 Feb 2025 14:18:16 GMT</pubDate>
    </item>    <item>
      <title>0.0.11</title>
      <link>https://pypi.org/project/envquest/0.0.11/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Sat, 25 Jan 2025 01:50:52 GMT</pubDate>
    </item>    <item>
      <title>0.0.10</title>
      <link>https://pypi.org/project/envquest/0.0.10/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Thu, 16 Jan 2025 02:53:03 GMT</pubDate>
    </item>    <item>
      <title>0.0.9</title>
      <link>https://pypi.org/project/envquest/0.0.9/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Sat, 11 Jan 2025 23:21:59 GMT</pubDate>
    </item>    <item>
      <title>0.0.8</title>
      <link>https://pypi.org/project/envquest/0.0.8/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Thu, 02 Jan 2025 23:17:04 GMT</pubDate>
    </item>    <item>
      <title>0.0.7</title>
      <link>https://pypi.org/project/envquest/0.0.7/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Thu, 02 Jan 2025 21:15:37 GMT</pubDate>
    </item>    <item>
      <title>0.0.4</title>
      <link>https://pypi.org/project/envquest/0.0.4/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Thu, 02 Jan 2025 17:16:53 GMT</pubDate>
    </item>    <item>
      <title>0.0.3</title>
      <link>https://pypi.org/project/envquest/0.0.3/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Thu, 02 Jan 2025 07:17:33 GMT</pubDate>
    </item>    <item>
      <title>0.0.2</title>
      <link>https://pypi.org/project/envquest/0.0.2/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Thu, 02 Jan 2025 07:10:48 GMT</pubDate>
    </item>    <item>
      <title>0.0.1</title>
      <link>https://pypi.org/project/envquest/0.0.1/</link>
      <description>A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.</description>
<author>medric49@gmail.com</author>      <pubDate>Thu, 02 Jan 2025 07:02:44 GMT</pubDate>
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