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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Inductive logic programming at 30 · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2102.10556/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2102.10556/feed.xml" rel="self" type="application/rss+xml" /><item><title>Inductive logic programming at 30 — mentioned by YeGoblynQueenne</title><link>https://news.ycombinator.com/item?id=41891610</link><guid isPermaLink="false">urn:hackerpapers:mention:2102.10556:41891610</guid><pubDate>Sat, 19 Oct 2024 23:24:03 GMT</pubDate><description>&lt;p&gt;Oh, I didn&amp;#x27;t remember that Bratko had a chapter on ILP. I&amp;#x27;ve met him in a couple of ILP conferences so I knew he&amp;#x27;s published work in ILP though [1]. The techniques described in the book are quite a bit older and, to be honest, they were rather limited, in particular with respect to learning recursion. There&amp;#x27;s a New Wave of ILP nowadays however and a flourishing of new approaches that followed from MIL, which kinda threw open the gates. There&amp;#x27;s a recent synopsis of the latest advances in ILP here: https://arxiv.org/pdf/2102.10556 &amp;gt;&amp;gt; With all the hot news in Prolog these days I&amp;#x27;d think you…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2102.10556/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Inductive logic programming at 30 — HN submission</title><link>https://news.ycombinator.com/item?id=36834317</link><guid isPermaLink="false">urn:hackerpapers:submission:2102.10556:36834317</guid><pubDate>Sun, 23 Jul 2023 11:17:03 GMT</pubDate><description>&lt;p&gt;Inductive Logic Programming At 30 (2022)&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2102.10556/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Inductive logic programming at 30 — mentioned by YeGoblynQueenne</title><link>https://news.ycombinator.com/item?id=30651649</link><guid isPermaLink="false">urn:hackerpapers:mention:2102.10556:30651649</guid><pubDate>Sat, 12 Mar 2022 14:36:09 GMT</pubDate><description>&lt;p&gt;I study Inductive Logic Programming (ILP) which is a kind of inductive program synthesis. Inductive program synthesis is learning from partial specifications, where deductive program synthesis is learning from complete specifications (compilation can be seen as a form of deductive program synthesis, for example). ILP studies algorithms that learn logic programs from examples. &amp;quot;Logic programs&amp;quot; as in programs in a language of the Logic Programming paradigm, such as Prolog or Answer Set Programming (ASP). If you&amp;#x27;re interested in program synthesis, this is the staple modern reference: Program…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2102.10556/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
