<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0">
  <channel>
    <title>PyPI recent updates for elsciRL</title>
    <link>https://pypi.org/project/elscirl/</link>
    <description>Recent updates to the Python Package Index for elsciRL</description>
    <language>en</language>    <item>
      <title>0.4.0</title>
      <link>https://pypi.org/project/elscirl/0.4.0/</link>
      <description>Apply language solutions to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Mon, 08 Dec 2025 18:43:43 GMT</pubDate>
    </item>    <item>
      <title>0.3.6</title>
      <link>https://pypi.org/project/elscirl/0.3.6/</link>
      <description>Apply language solutions to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Sat, 05 Jul 2025 18:25:45 GMT</pubDate>
    </item>    <item>
      <title>0.3.5</title>
      <link>https://pypi.org/project/elscirl/0.3.5/</link>
      <description>Apply language solutions to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Sat, 05 Jul 2025 18:07:50 GMT</pubDate>
    </item>    <item>
      <title>0.3.4</title>
      <link>https://pypi.org/project/elscirl/0.3.4/</link>
      <description>Apply language solutions to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Sat, 05 Jul 2025 18:05:42 GMT</pubDate>
    </item>    <item>
      <title>0.3.3</title>
      <link>https://pypi.org/project/elscirl/0.3.3/</link>
      <description>Apply language solutions to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Sat, 05 Jul 2025 17:51:20 GMT</pubDate>
    </item>    <item>
      <title>0.3.2</title>
      <link>https://pypi.org/project/elscirl/0.3.2/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Thu, 29 May 2025 12:21:22 GMT</pubDate>
    </item>    <item>
      <title>0.3.1</title>
      <link>https://pypi.org/project/elscirl/0.3.1/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Mon, 05 May 2025 18:56:55 GMT</pubDate>
    </item>    <item>
      <title>0.3.0</title>
      <link>https://pypi.org/project/elscirl/0.3.0/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Fri, 25 Apr 2025 08:38:27 GMT</pubDate>
    </item>    <item>
      <title>0.2.7</title>
      <link>https://pypi.org/project/elscirl/0.2.7/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Fri, 25 Apr 2025 08:14:59 GMT</pubDate>
    </item>    <item>
      <title>0.2.6</title>
      <link>https://pypi.org/project/elscirl/0.2.6/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Thu, 30 Jan 2025 18:06:29 GMT</pubDate>
    </item>    <item>
      <title>0.2.52</title>
      <link>https://pypi.org/project/elscirl/0.2.52/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Mon, 20 Jan 2025 13:01:41 GMT</pubDate>
    </item>    <item>
      <title>0.2.5</title>
      <link>https://pypi.org/project/elscirl/0.2.5/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Mon, 20 Jan 2025 12:54:27 GMT</pubDate>
    </item>    <item>
      <title>0.2.4</title>
      <link>https://pypi.org/project/elscirl/0.2.4/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Mon, 20 Jan 2025 12:16:17 GMT</pubDate>
    </item>    <item>
      <title>0.2.3</title>
      <link>https://pypi.org/project/elscirl/0.2.3/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Mon, 20 Jan 2025 12:14:33 GMT</pubDate>
    </item>    <item>
      <title>0.2.2</title>
      <link>https://pypi.org/project/elscirl/0.2.2/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Mon, 20 Jan 2025 10:32:03 GMT</pubDate>
    </item>    <item>
      <title>0.2.1</title>
      <link>https://pypi.org/project/elscirl/0.2.1/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Mon, 20 Jan 2025 10:13:04 GMT</pubDate>
    </item>    <item>
      <title>0.2.0</title>
      <link>https://pypi.org/project/elscirl/0.2.0/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Fri, 17 Jan 2025 17:14:55 GMT</pubDate>
    </item>    <item>
      <title>0.1.7</title>
      <link>https://pypi.org/project/elscirl/0.1.7/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Thu, 09 Jan 2025 15:54:01 GMT</pubDate>
    </item>    <item>
      <title>0.1.6</title>
      <link>https://pypi.org/project/elscirl/0.1.6/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 15:28:29 GMT</pubDate>
    </item>    <item>
      <title>0.1.5</title>
      <link>https://pypi.org/project/elscirl/0.1.5/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:39:12 GMT</pubDate>
    </item>    <item>
      <title>0.1.49</title>
      <link>https://pypi.org/project/elscirl/0.1.49/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:26:34 GMT</pubDate>
    </item>    <item>
      <title>0.1.48</title>
      <link>https://pypi.org/project/elscirl/0.1.48/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:23:07 GMT</pubDate>
    </item>    <item>
      <title>0.1.47</title>
      <link>https://pypi.org/project/elscirl/0.1.47/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:17:01 GMT</pubDate>
    </item>    <item>
      <title>0.1.46</title>
      <link>https://pypi.org/project/elscirl/0.1.46/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:14:24 GMT</pubDate>
    </item>    <item>
      <title>0.1.45</title>
      <link>https://pypi.org/project/elscirl/0.1.45/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:11:17 GMT</pubDate>
    </item>    <item>
      <title>0.1.44</title>
      <link>https://pypi.org/project/elscirl/0.1.44/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:07:23 GMT</pubDate>
    </item>    <item>
      <title>0.1.43</title>
      <link>https://pypi.org/project/elscirl/0.1.43/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:03:01 GMT</pubDate>
    </item>    <item>
      <title>0.1.42</title>
      <link>https://pypi.org/project/elscirl/0.1.42/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 10:00:56 GMT</pubDate>
    </item>    <item>
      <title>0.1.41</title>
      <link>https://pypi.org/project/elscirl/0.1.41/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 09:43:13 GMT</pubDate>
    </item>    <item>
      <title>0.1.4</title>
      <link>https://pypi.org/project/elscirl/0.1.4/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 09:39:40 GMT</pubDate>
    </item>    <item>
      <title>0.1.3</title>
      <link>https://pypi.org/project/elscirl/0.1.3/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 09:37:26 GMT</pubDate>
    </item>    <item>
      <title>0.1.2</title>
      <link>https://pypi.org/project/elscirl/0.1.2/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 09:36:12 GMT</pubDate>
    </item>    <item>
      <title>0.1.1</title>
      <link>https://pypi.org/project/elscirl/0.1.1/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Wed, 08 Jan 2025 09:32:53 GMT</pubDate>
    </item>    <item>
      <title>0.1.0</title>
      <link>https://pypi.org/project/elscirl/0.1.0/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Fri, 03 Jan 2025 16:42:17 GMT</pubDate>
    </item>    <item>
      <title>0.0.9</title>
      <link>https://pypi.org/project/elscirl/0.0.9/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Tue, 17 Dec 2024 15:48:40 GMT</pubDate>
    </item>    <item>
      <title>0.0.8</title>
      <link>https://pypi.org/project/elscirl/0.0.8/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Fri, 06 Dec 2024 15:03:17 GMT</pubDate>
    </item>    <item>
      <title>0.0.7</title>
      <link>https://pypi.org/project/elscirl/0.0.7/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Fri, 06 Dec 2024 14:44:16 GMT</pubDate>
    </item>    <item>
      <title>0.0.6</title>
      <link>https://pypi.org/project/elscirl/0.0.6/</link>
      <description>Applying the elsciRL architecture to Reinforcement Learning problems.</description>
<author>pdfosborne@gmail.com</author>      <pubDate>Fri, 29 Nov 2024 12:23:40 GMT</pubDate>
    </item>  </channel>
</rss>