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    <title>PyPI recent updates for pypddl-datasets</title>
    <link>https://pypi.org/project/pypddl-datasets/</link>
    <description>Recent updates to the Python Package Index for pypddl-datasets</description>
    <language>en</language>    <item>
      <title>0.0.7</title>
      <link>https://pypi.org/project/pypddl-datasets/0.0.7/</link>
      <description>Download PDDL planning benchmark suites: classical, numeric, profiling, and learning splits.</description>
<author>dominik.drexler@liu.se</author>      <pubDate>Sun, 12 Jul 2026 17:01:54 GMT</pubDate>
    </item>    <item>
      <title>0.0.6</title>
      <link>https://pypi.org/project/pypddl-datasets/0.0.6/</link>
      <description>Download PDDL planning benchmark suites: classical, numeric, profiling, and learning splits.</description>
<author>dominik.drexler@liu.se</author>      <pubDate>Sun, 12 Jul 2026 14:43:51 GMT</pubDate>
    </item>    <item>
      <title>0.0.5</title>
      <link>https://pypi.org/project/pypddl-datasets/0.0.5/</link>
      <description>Download PDDL planning benchmark suites: classical, numeric, profiling, and learning splits.</description>
<author>dominik.drexler@liu.se</author>      <pubDate>Sun, 12 Jul 2026 12:59:50 GMT</pubDate>
    </item>    <item>
      <title>0.0.4</title>
      <link>https://pypi.org/project/pypddl-datasets/0.0.4/</link>
      <description>Download PDDL planning benchmark suites: classical, numeric, profiling, and learning splits.</description>
<author>dominik.drexler@liu.se</author>      <pubDate>Sun, 12 Jul 2026 11:58:05 GMT</pubDate>
    </item>    <item>
      <title>0.0.3</title>
      <link>https://pypi.org/project/pypddl-datasets/0.0.3/</link>
      <description>Download PDDL planning benchmark suites: classical, numeric, profiling, and learning splits.</description>
<author>dominik.drexler@liu.se</author>      <pubDate>Sun, 12 Jul 2026 07:38:11 GMT</pubDate>
    </item>    <item>
      <title>0.0.2</title>
      <link>https://pypi.org/project/pypddl-datasets/0.0.2/</link>
      <description>Download PDDL planning benchmark suites: classical, numeric, profiling, and learning splits.</description>
<author>dominik.drexler@liu.se</author>      <pubDate>Sun, 12 Jul 2026 07:28:27 GMT</pubDate>
    </item>    <item>
      <title>0.0.1</title>
      <link>https://pypi.org/project/pypddl-datasets/0.0.1/</link>
      <description>Download PDDL planning benchmark suites: classical, numeric, profiling, and learning splits.</description>
<author>dominik.drexler@liu.se</author>      <pubDate>Sat, 11 Jul 2026 21:43:14 GMT</pubDate>
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