<?xml version="1.0" encoding="utf-8"?><rss version="2.0"><channel><title>RSS for Propagation in Constraints: How One Thing Leads to Another</title><link>http://academic.research.microsoft.com/Rss.aspx?cata=9&amp;id=39260765</link><description>Search RSS feed for Microsoft Academic Search</description><generator>MSRA Libra RSS Burner</generator><copyright>(c)2008 Microsoft Corpration, All right reserved.</copyright><pubDate>Thu, 23 May 2013 18:00:54 GMT</pubDate><lastBuildDate>Thu, 23 May 2013 18:00:54 GMT</lastBuildDate><category /><item><title>Propagation in Constraints: How One Thing Leads to Another</title><link>http://academic.research.microsoft.com/Publication/39260765</link><pubDate>Thu, 23 May 2013 11:00:54 GMT</pubDate><guid isPermaLink="false">392607650</guid><description><![CDATA[<div><a href="http://academic.research.microsoft.com/Author/20342">Ian P. Gent</a>:
            
            <span style="margin-left:20px" /><span style="margin-left:20px"><a href="http://www.springerlink.com/content/071413773u051752">view publication</a></span></div><div> At a conference such as CPAIOR, we have experts from many different approaches to searching huge combinatorial spaces. Much of what we all do is common, for example similar search methods, heuristics, and learning techniques. So what is it that is essentially different about <a href='http://academic.research.microsoft.com/Keyword/7569/constraint-programming'>Constraint Programming</a>  in particular? One answer is the power and diversity of <a href='http://academic.research.microsoft.com/Keyword/7571/constraint-propagation'>constraint propagation</a>  algorithms. By contrast, other search disciplines often rely on just one propagation technique, such as unit propagation in SAT. </div><div>Conference: <a href="http://academic.research.microsoft.com/Conference/1881">International Conference on Integration of AI and OR Techniques in Constraint Programming - CPAIOR</a>, 2011</div><div></div><div />]]></description></item></channel></rss>