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<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Thinking Clearly - Latest Comments in Witchly interlude: SPASSing out</title><link>http://clarkparsia.disqus.com/</link><description>Semantics: OWL, RDF, etc.</description><atom:link href="https://clarkparsia.disqus.com/witchly_interlude_spassing_out/latest.rss" rel="self"></atom:link><language>en</language><lastBuildDate>Wed, 03 Jan 2007 22:55:31 -0000</lastBuildDate><item><title>Re: Witchly interlude: SPASSing out</title><link>http://clarkparsia.com/weblog/2007/01/03/witchly-interlude-spassing-out/#comment-1446931</link><description>&lt;p&gt;I'll be using a ground semantic calculus, since that's what's most commonly used in DL reasoners. I suppose I could do a free variable one as well, which will pop in unification.&lt;/p&gt;&lt;p&gt;RETE and LP (by which I presume you mean logic programming) don't &lt;em&gt;most&lt;/em&gt; naturally conflate in my lexicon. The bog standard framework for LP is resolution, from Prolog and Datalog to disjunctive datalog and answer set programming.&lt;/p&gt;&lt;p&gt;But the most natural metric would be performance, I would think :)&lt;/p&gt;&lt;p&gt;And do you mean "optimizations" by "heuristics"? Many optimizations are not heuristic, at least not in how I understand "heuristic".&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Bijan Parsia</dc:creator><pubDate>Wed, 03 Jan 2007 22:55:31 -0000</pubDate></item><item><title>Re: Witchly interlude: SPASSing out</title><link>http://clarkparsia.com/weblog/2007/01/03/witchly-interlude-spassing-out/#comment-1446928</link><description>&lt;p&gt;I'd be curious to see how a tableau proof compares to a resolution-based proof.  "AI: A Modern Approach" has a nice unification heuristic [1] (in python as well) for a backward chaining algorithm which is similar to how prolog unifies and the basis for Deroo's euler-enhanced resolution mechanism for proof and backward chaining.&lt;/p&gt;&lt;p&gt;I've recently pondered hooking up the python RETE-UL [2] implementation I've been playing with a means to track a non-circular path through the RETE network as an alternative proof generation mechanism for large rulesets and factbases.  I wonder if there is some metric for comparing the application of LP heuristics to DLP reasoning against (more traditional) resolution and tableux-based heuristics for the same KR.&lt;/p&gt;&lt;p&gt;Generated proofs, whether or not they are truely valuable, bring about a certain unmatchable satisfaction to a logician =)&lt;/p&gt;&lt;p&gt;[1] &lt;a href="http://aima.cs.berkeley.edu/python/logic.html" rel="nofollow noopener" target="_blank" title="http://aima.cs.berkeley.edu/python/logic.html"&gt;http://aima.cs.berkeley.edu...&lt;/a&gt;&lt;br&gt;[2] &lt;a href="http://reports-archive.adm.cs.cmu.edu/anon/1995/CMU-CS-95-113.pdf" rel="nofollow noopener" target="_blank" title="http://reports-archive.adm.cs.cmu.edu/anon/1995/CMU-CS-95-113.pdf"&gt;http://reports-archive.adm....&lt;/a&gt;&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chimezie</dc:creator><pubDate>Wed, 03 Jan 2007 19:42:54 -0000</pubDate></item></channel></rss>