P vs NP

The Road to Conscious Machines

by Michael Wooldridge  · 2 Nov 2018  · 346pp  · 97,890 words

NP-complete problems can be efficiently solved is, in fact, one of the most important open problems in science today. It is known as the P vs NP problem,17 and if you can settle it one way or the other to the satisfaction of the scientific community, you stand to receive a

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. The theory of NP-completeness was developed in the 1970s, and in this time many AI problems were discovered to be NP-complete. See also P vs NP problem. ontological engineering In an expert system (and, more generally, in a knowledge-based system), this is the task of defining the conceptual vocabulary you

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have no way of being able to tell what those weights ‘mean’. This means that current neural nets can’t explain or justify their decisions. P vs NP problem The question of whether NP-complete problems definitely can or cannot always be solved efficiently. One of the biggest open problems in mathematics today

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. Not likely to be settled any time soon. (‘P’ stands for ‘polynomial time’; ‘NP’ stands for ‘non-deterministic polynomial time’: technically, the P vs NP problem is whether problems that can be solved in non-deterministic polynomial time can be solved in polynomial time.) perception The process of understanding what

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efficient algorithm to solve it. NP-complete problems are not tractable: we don’t have algorithms that are guaranteed to solve them efficiently. See also P vs NP problem. training (in machine learning) The task of a machine learning program is to learn associations between inputs and outputs without being told how to

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solve a problem is one that has ‘polynomial running time’. See the Further Reading section for pointers to the literature on NP-completeness and the P vs NP problem. * * * CHAPTER 3: KNOWLEDGE IS POWER 1. P. Winston and B. Horn. LISP (3rd edn). Pearson, 1989. 2. E. H. Shortliffe. Computer-Based Medical Consultation

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norms 260 NP-complete problems 81–5, 164–5 nuclear energy 242–3 nuclear fusion 305 O ontological engineering 117 Osborne, Michael 268–70 P P vs NP problem 83 paperclips 261 Papert, Seymour 180 Parallel Distributed Processing (PDP) 182–4 Pepper 299 perception 54 perceptron models 174–81, 183 Perceptrons (Minsky & Papert

Journey to the Edge of Reason: The Life of Kurt Gödel

by Stephen Budiansky  · 10 May 2021  · 406pp  · 108,266 words

of the most fundamental questions of computer science. Gödel’s letter to his dying colleague was apparently the very first formulation of the so-called “P vs. NP” problem, which offered a striking analogy of his Incompleteness Theorem to the field of computing. “P” is the set of problems easy to solve, for

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, 185, 188, 189 Old Catholics, 49 ontological proof, 268–69 Oppenheim, Paul, 216 Oppenheimer, J. Robert, 237–38, 247–48, 249, 251 Orient Express, 145 P vs. NP problem, 258 Palace of Justice attack, 86, 87 Palacký, František, 17–18 paradoxes Incompleteness Theorem and, 130, 135, 267 set theory and, 109–10, 111

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KG dictates Continuum Hypothesis result to, 177, 190 KG’s career, advocacy and support for, 106, 189, 201, 234, 238–39, 248 Morgenstern and, 219 P vs. NP problem and, 258 paralysis and death, 258, 274 also mentioned, 192, 236, 244 von Neumann, Klári, 147, 151, 156, 157 von Schönerer, Georg, 34 Wagner

Average Is Over: Powering America Beyond the Age of the Great Stagnation

by Tyler Cowen  · 11 Sep 2013  · 291pp  · 81,703 words

, 96, 98 matchmaking. See online dating mathematics and complexity of theories, 212 and division of labor, 207–8 math education, 183–84 mathematical economics, 222 “P vs. NP” problem, 101 and prodigies, 216 theorem development, 206–8 Mayhew, Henry, 33–34, 36 Mayo Clinic, 87 McAfee, Andrew, 6 McGonigal, Jane, 187 McGovern, George

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, 16, 95–98, 125, 144–45 online education, 179–85 opportunity cost, 184 options-pricing theory, 203 outsourcing, 162, 163–71 overseas labor markets, 59 “P vs. NP” problem, 101 particle physics, 211–15 patent law, 17 per capita income, 170 Perelman, Grigory, 208 performance evaluation, 104 Peri, Giovanni, 162–63 “the periphery

Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room

by David Weinberger  · 14 Jul 2011  · 369pp  · 80,355 words

originally formulated the problem emailed Deolalikar’s solution to some of his colleagues, saying, “This appears to be a relatively serious claim to have solved P vs. NP.” This highly authoritative endorsement made the paper go viral, at least within the limited world of mathematicians interested in such matters. Unfortunately, within two days

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Onion newspaper Opacity of expertise Open filters Open Government Initiative Open access movement OpenCourseWare OpenGov site Open-notebook science Ordering the universe: humors Organizational efficiency “P vs. NP” problem “Packard Goose” (song) Page, Scott Pandora’s Hope: Essays on the Reality of Science Studies (Latour) Paper-based knowledge: stopping points for knowledge. See

Peer-to-Peer

by Andy Oram  · 26 Feb 2001  · 673pp  · 164,804 words

tied up with the “P vs. NC” problem in computational complexity theory and is outside the scope of this chapter. Similar to the better known “P vs. NP” problem, which concerns the question, “Which problems are easy?” the P vs. NC problem asks, “Which problems are parallelizable?”[56] Fungible micropayments All of the

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messaging services, Central control and local autonomy P P in P2P is People, File sharing: Napster and successors P vs. NC problem, Nonparallelizable work functions P vs. NP problem, Nonparallelizable work functions P2P directory (O’Reilly Network), Remaking the Peer-to-Peer Meme packet delivery, best effort, The TCP rate equation: Cooperative protocols

Reinventing Discovery: The New Era of Networked Science

by Michael Nielsen  · 2 Oct 2011  · 400pp  · 94,847 words

of science: Its political and economic theory. Minerva, 1:54–74, 1962. http://www.missouriwestern.edu/orgs/polanyi/mp-repsc.htm. [173] Polymath participants. Deolalikar P vs NP paper. Polymath wiki, 2010-. http://michaelnielsen.org/polymath1/index.php?title=Deolalikar’s_P!%3DNP_paper. [174] Zoran Popović. CASP8 results. Foldit blog, December 17