Examples of using Complexity theory in English and their translations into Romanian
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Complexity theory, chains.
No posts with label complexity theory.
In computational complexity theory, Karp's 21 NP-complete problems are a set of computational problems which are NP-complete.
Now that I have got your attention, complexity theory.
His current research interests include complexity theory( especially agent-based modeling), and international security.
Studying their abstract properties yields many insights into computer science and complexity theory.
We're not back in a complexity theory class, Ada.
You know, the geometrical construct of that game has applications in Computational Complexity Theory.
Complexity theory considers not only whether a problem can be solved at all on a computer, but also how efficiently the problem can be solved.
This was proved by Gabriel Lamé in 1844, andmarks the beginning of computational complexity theory.
You don't work your entire academic life in the fields of theoretical computer science and complexity theory without understanding the-- the massive implications of doing something like this.
P=np is the most significant problem in theoretical computer science and mathematical complexity theory.
This proof, published by Gabriel Lamé in 1844,represents the beginning of computational complexity theory, and also the first practical application of the Fibonacci numbers.
The first one(chronologically) is used in analytic number theory, and the other one in computational complexity theory.
It is a common andreasonably accurate assumption in complexity theory; however, it has some caveats.
Papadimitriou is the author of the textbook Computational Complexity, one of the most widely used textbooks in the field of computational complexity theory.
He became fellow of the U.S. National Academy of Engineering for contributions to complexity theory, database theory, and combinatorial optimization.[7] In 2009 he was elected to the US National Academy of Sciences.
What's actually useful for mathematicians, and by extension, mankind,are the foundational proofs upon which complexity theory-- mathematics--is based.
There are also substantial connections with complexity theory, mathematical logic, the study of Lie Groups and their discrete subgroups, dynamical systems, probability theory, K-theory, and other areas of mathematics.
In 1984 Gell-Mann co-founded the Santa Fe Institute-a non-profit theoretical research institute in Santa Fe, New Mexico-to study complex systems anddisseminate the notion of a separate interdisciplinary study of complexity theory.
The relation between the complexity classes P andNP is studied in computational complexity theory, the part of the theory of computation dealing with the resources required during computation to solve a given problem.
A proof that showed that P≠ NP would lack the practical computational benefits of aproof that P= NP, but would nevertheless represent a very significant advance in computational complexity theory and provide guidance for future research.
NP-hardness(non-deterministic polynomial-time hard),in computational complexity theory, is the defining property of a class of problems that are, informally,"at least as hard as the hardest problems in NP".
The problem often arises in resource allocation where there are financial constraints and is studied in fields such as combinatorics,computer science, complexity theory, cryptography, applied mathematics, and daily fantasy sports.
James Glattfelder studies complexity: how an interconnected system-- say, a swarm of birds-- is more than the sum of its parts.And complexity theory, it turns out, can reveal a lot about how the economy works. Glattfelder shares a groundbreaking study of how control flows through the global economy, and how concentration of power in the hands of a shockingly small number leaves us all vulnerable.
Its theories and models are being developed andrefined in universities around the world building on some of the best new research in economics, complexity theory, evolutionary theory, psychology, anthropology and other disciplines.
In computational complexity theory, L(also known as LSPACE or DLOGSPACE) is the complexity class containing decision problems that can be solved by a deterministic Turing machine using a logarithmic amount of writable memory space.[1][2] Formally, the Turing machine has two tapes, one of which encodes the input and can only be read, whereas the other tape has logarithmic size but can be read as well as written.
As additional evidence for the difficulty of the problem,essentially all known proof techniques in computational complexity theory fall into one of the following classifications, each of which is known to be insufficient to prove that P≠ NP.
Richard Edwin Stearns(born July 5, 1936) is a prominent computer scientist who,with Juris Hartmanis, received the 1993 ACM Turing Award"in recognition of their seminal paper which established the foundations for the field of computational complexity theory"(Hartmanis and Stearns, 1965).
The field is divided into three major branches: automata theory and language, computability theory, and computational complexity theory, which are linked by the question:"What are the fundamental capabilities and limitations of computers?".[1].