If the result stands, it would prove that the two classes P and NP are not identical, and impose severe limits on what computers can accomplish – implying that many tasks may be fundamentally, irreducibly complex.
For some problems – including factorisation – the result does not clearly say whether they can be solved quickly. But a huge sub-class of problems called "NP-complete" would be doomed. A famous example is the travelling salesman problem – finding the shortest route between a set of cities. Such problems can be checked quickly, but if P ≠ NP then there is no computer program that can complete them quickly from scratch.
Complexity theorists have given a favourable reception to Deolalikar's draft paper, but when the final version is released in a week's time the process of checking it will intensify.
Wendell Wallach and Colin Allen maintain this blog on the theory and development of artificial moral agents and computational ethics, topics covered in their OUP 2009 book...
Friday, August 20, 2010
P ≠ NP? Limits on Computing?
An August 10th article in the NewScientist titled, P ≠ NP? It's bad news for the power of computing, reports that a mathematician Vinay Deolalikar has perhaps solved a major computational problem.
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The proof is flawed, according to Fields Medalist Terence Tao and many others.
http://en.wikipedia.org/wiki/Vinay_Deolalikar#Deolalikar
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