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    <title>PyPI recent updates for atarihns</title>
    <link>https://pypi.org/project/atarihns/</link>
    <description>Recent updates to the Python Package Index for atarihns</description>
    <language>en</language>    <item>
      <title>1.0.1</title>
      <link>https://pypi.org/project/atarihns/1.0.1/</link>
      <description>A helper to calculate human normalized score for different atari environments efficiently and easily.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Tue, 28 Apr 2026 11:11:53 GMT</pubDate>
    </item>    <item>
      <title>0.0.18</title>
      <link>https://pypi.org/project/atarihns/0.0.18/</link>
      <description>A helper to calculate human normalized score for different atari environments efficiently and easily.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Fri, 10 Apr 2026 15:24:31 GMT</pubDate>
    </item>    <item>
      <title>0.0.17</title>
      <link>https://pypi.org/project/atarihns/0.0.17/</link>
      <description>A little helper to calculate human normalized score for different ALE environments efficiently.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Wed, 07 Jan 2026 13:56:31 GMT</pubDate>
    </item>    <item>
      <title>0.0.16</title>
      <link>https://pypi.org/project/atarihns/0.0.16/</link>
      <description>A little helper to calculate human normalized score for different ALE environments efficiently.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Mon, 24 Nov 2025 14:11:48 GMT</pubDate>
    </item>    <item>
      <title>0.0.15</title>
      <link>https://pypi.org/project/atarihns/0.0.15/</link>
      <description>A little helper to calculate human normalized score for different ALE environments efficiently.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Mon, 24 Nov 2025 14:10:44 GMT</pubDate>
    </item>    <item>
      <title>0.0.14</title>
      <link>https://pypi.org/project/atarihns/0.0.14/</link>
      <description>A little helper to calculate human normalized score for different ALE environments efficiently.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Mon, 24 Nov 2025 10:09:59 GMT</pubDate>
    </item>    <item>
      <title>0.0.13</title>
      <link>https://pypi.org/project/atarihns/0.0.13/</link>
      <description>A little helper to calculate human normalized score for different ALE environments efficiently.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Mon, 24 Nov 2025 10:05:44 GMT</pubDate>
    </item>    <item>
      <title>0.0.12</title>
      <link>https://pypi.org/project/atarihns/0.0.12/</link>
      <description>A little helper to calculate human normalized score for different ALE environments efficiently.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Mon, 24 Nov 2025 10:04:51 GMT</pubDate>
    </item>    <item>
      <title>0.0.11</title>
      <link>https://pypi.org/project/atarihns/0.0.11/</link>
      <description>A little helper to calculate human normalized score for different ALE environments efficiently.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Mon, 24 Nov 2025 10:03:54 GMT</pubDate>
    </item>    <item>
      <title>0.0.1</title>
      <link>https://pypi.org/project/atarihns/0.0.1/</link>
      <description>Sum tree and min tree implementation used particularly in reinforcement learning algorithms.</description>
<author>tahashieenavaz@gmail.com</author>      <pubDate>Mon, 24 Nov 2025 09:59:59 GMT</pubDate>
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