UP (complexity) - definição. O que é UP (complexity). Significado, conceito
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O que (quem) é UP (complexity) - definição

COMPLEXITY CLASS OF DECISION PROBLEMS SOLVABLE IN POLYNOMIAL TIME ON AN UNAMBIGUOUS TURING MACHINE WITH AT MOST ONE ACCEPTING PATH FOR EACH INPUT

UP (complexity)         
In complexity theory, UP (unambiguous non-deterministic polynomial-time) is the complexity class of decision problems solvable in polynomial time on an unambiguous Turing machine with at most one accepting path for each input. UP contains P and is contained in NP.
Computational complexity         
MEASURE OF THE AMOUNT OF RESOURCES NEEDED TO RUN AN ALGORITHM OR SOLVE A COMPUTATIONAL PROBLEM
Asymptotic complexity; Computational Complexity; Bit complexity; Context of computational complexity; Complexity of computation (bit); Computational complexities
In computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements.
complexity         
PROFESSIONAL ESPORTS ORGANIZATION BASED IN THE UNITED STATES
Los Angeles Complexity; CompLexity Gaming; LA Complexity; Complexity LA; CompLexity; Team CompLexity; CoL.Black; CoL
<algorithm> The level in difficulty in solving mathematically posed problems as measured by the time, number of steps or arithmetic operations, or memory space required (called time complexity, computational complexity, and space complexity, respectively). The interesting aspect is usually how complexity scales with the size of the input (the "scalability"), where the size of the input is described by some number N. Thus an algorithm may have computational complexity O(N^2) (of the order of the square of the size of the input), in which case if the input doubles in size, the computation will take four times as many steps. The ideal is a constant time algorithm (O(1)) or failing that, O(N). See also NP-complete. (1994-10-20)

Wikipédia

UP (complexity)

In complexity theory, UP (unambiguous non-deterministic polynomial-time) is the complexity class of decision problems solvable in polynomial time on an unambiguous Turing machine with at most one accepting path for each input. UP contains P and is contained in NP.

A common reformulation of NP states that a language is in NP if and only if a given answer can be verified by a deterministic machine in polynomial time. Similarly, a language is in UP if a given answer can be verified in polynomial time, and the verifier machine only accepts at most one answer for each problem instance. More formally, a language L belongs to UP if there exists a two-input polynomial-time algorithm A and a constant c such that

if x in L , then there exists a unique certificate y with | y | = O ( | x | c ) {\displaystyle |y|=O(|x|^{c})} such that A ( x , y ) = 1 {\displaystyle A(x,y)=1}
if x is not in L, there is no certificate y with | y | = O ( | x | c ) {\displaystyle |y|=O(|x|^{c})} such that A ( x , y ) = 1 {\displaystyle A(x,y)=1}
algorithm A verifies L in polynomial time.

UP (and its complement co-UP) contain both the integer factorization problem and parity game problem; because determined effort has yet to find a polynomial-time solution to any of these problems, it is suspected to be difficult to show P=UP, or even P=(UPco-UP).

The Valiant–Vazirani theorem states that NP is contained in RPPromise-UP, which means that there is a randomized reduction from any problem in NP to a problem in Promise-UP.

UP is not known to have any complete problems.