Solving NP-Complete Problems?

In preparing for the interview with the Java-based Drools Planner on FLOSS Weekly, my attention was grabbed by the claim it can solve NP-complete problems. You’ll need to watch the show to see how that worked out!

[youtube http://www.youtube.com/watch?v=sL-URSfYduA]
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One Response

  1. Here I thought NP-completeness was deprecated in favor of orders of phi/omega/1. Free advice with Greek got taken off the ‘worth a dollar’ currency in more than one domain, (euro, higher education) so heuristically I guess that means we use nP as a fallback?

    The brag appears correct; even if you do not encapsulate rules like the key being the same despite leaks from before a nontrivial seed (0000000000000100, 1234567, 0) and its computational load were activated, rambling tropes (how many ways can you say ‘MLP:FIM is haram’ in a Regional English) because the metaplanner abstracts to polynomial time (hello brute force) just great. It is surely busily classifying transactions as laundering, growth, overexertion, hedged, etc.

    The thing would be to get this J2EE to-do on a flash+logic chip optimized for a reasonable reliability versus the lifetime of the front end! Users plug in Fermat’s last margin doodle or somesuch and compare the output to some of Andrew Wiles’ work, move onto partial elliptical solution spaces, and check that they are not landing their modeling confirmation biases, check for prior work, then use the Lickable Multiverse Planner function of the app to make wishes. Because Grindr (OkCupid, etc.) looks too easy.

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