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46 relations: Algorithm, ALL (complexity), Alphabet (formal languages), Boolean satisfiability problem, Co-NP-complete, Complement (complexity), Complete (complexity), Complexity class, Computability theory, Computational complexity theory, Computational problem, Computational resource, Counting problem (complexity), Daniel Kroening, Decidability (logic), Effective method, Formal language, Function problem, Gödel numbering, Halting problem, Hartley Rogers Jr., Indicator function, Infinite set, Linear programming, List of undecidable problems, Long division, Many-one reduction, Michael Sipser, Model theory, NP (complexity), NP-completeness, Operations research, Partial function, Polynomial-time reduction, Primality test, Recursive set, Recursively enumerable set, Search problem, String (computer science), Time complexity, Travelling salesman problem, Turing degree, Undecidable problem, Word problem (mathematics), Yes–no question, Zohar Manna.
Algorithm
In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.
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ALL (complexity)
In computability and complexity theory, ALL is the class of all decision problems.
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Alphabet (formal languages)
In formal language theory, a string is defined as a finite sequence of members of an underlying base set; this set is called the alphabet of a string or collection of strings.
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Boolean satisfiability problem
In computer science, the Boolean satisfiability problem (sometimes called propositional satisfiability problem and abbreviated as SATISFIABILITY or SAT) is the problem of determining if there exists an interpretation that satisfies a given Boolean formula.
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Co-NP-complete
In complexity theory, computational problems that are co-NP-complete are those that are the hardest problems in co-NP, in the sense that any problem in co-NP can be reformulated as a special case of any co-NP-complete problem with only polynomial overhead.
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Complement (complexity)
In computational complexity theory, the complement of a decision problem is the decision problem resulting from reversing the yes and no answers.
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Complete (complexity)
In computational complexity theory, a computational problem is complete for a complexity class if it is, in a technical sense, among the "hardest" (or "most expressive") problems in the complexity class.
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Complexity class
In computational complexity theory, a complexity class is a set of problems of related resource-based complexity.
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Computability theory
Computability theory, also known as recursion theory, is a branch of mathematical logic, of computer science, and of the theory of computation that originated in the 1930s with the study of computable functions and Turing degrees.
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Computational complexity theory
Computational complexity theory is a branch of the theory of computation in theoretical computer science that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other.
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Computational problem
In theoretical computer science, a computational problem is a mathematical object representing a collection of questions that computers might be able to solve.
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Computational resource
In computational complexity theory, a computational resource is a resource used by some computational models in the solution of computational problems.
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Counting problem (complexity)
In computational complexity theory and computability theory, a counting problem is a type of computational problem.
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Daniel Kroening
Daniel Kroening (born November 6, 1975https://subs.emis.de/LNI/Dissertation/Dissertation2/GI-Dissertations.02-7.pdf p. 80) is a German computer scientist, professor in computer science at the University of Oxford.
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Decidability (logic)
In logic, the term decidable refers to the decision problem, the question of the existence of an effective method for determining membership in a set of formulas, or, more precisely, an algorithm that can and will return a boolean true or false value that is correct (instead of looping indefinitely, crashing, returning "don't know" or returning a wrong answer).
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Effective method
In logic, mathematics and computer science, especially metalogic and computability theory, an effective methodHunter, Geoffrey, Metalogic: An Introduction to the Metatheory of Standard First-Order Logic, University of California Press, 1971 or effective procedure is a procedure for solving a problem from a specific class.
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Formal language
In mathematics, computer science, and linguistics, a formal language is a set of strings of symbols together with a set of rules that are specific to it.
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Function problem
In computational complexity theory, a function problem is a computational problem where a single output (of a total function) is expected for every input, but the output is more complex than that of a decision problem.
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Gödel numbering
In mathematical logic, a Gödel numbering is a function that assigns to each symbol and well-formed formula of some formal language a unique natural number, called its Gödel number.
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Halting problem
In computability theory, the halting problem is the problem of determining, from a description of an arbitrary computer program and an input, whether the program will finish running (i.e., halt) or continue to run forever.
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Hartley Rogers Jr.
Hartley Rogers Jr. (1926–2015) was a mathematician who worked in recursion theory, and was a professor in the Mathematics Department of the Massachusetts Institute of Technology.
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Indicator function
In mathematics, an indicator function or a characteristic function is a function defined on a set X that indicates membership of an element in a subset A of X, having the value 1 for all elements of A and the value 0 for all elements of X not in A. It is usually denoted by a symbol 1 or I, sometimes in boldface or blackboard boldface, with a subscript specifying the subset.
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Infinite set
In set theory, an infinite set is a set that is not a finite set.
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Linear programming
Linear programming (LP, also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships.
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List of undecidable problems
In computability theory, an undecidable problem is a type of computational problem that requires a yes/no answer, but where there cannot possibly be any computer program that always gives the correct answer; that is, any possible program would sometimes give the wrong answer or run forever without giving any answer.
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Long division
In arithmetic, long division is a standard division algorithm suitable for dividing multidigit numbers that is simple enough to perform by hand.
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Many-one reduction
In computability theory and computational complexity theory, a many-one reduction is a reduction which converts instances of one decision problem into instances of a second decision problem.
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Michael Sipser
Michael Fredric Sipser (born September 17, 1954) is a theoretical computer scientist who has made early contributions to computational complexity theory.
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Model theory
In mathematics, model theory is the study of classes of mathematical structures (e.g. groups, fields, graphs, universes of set theory) from the perspective of mathematical logic.
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NP (complexity)
In computational complexity theory, NP (for nondeterministic polynomial time) is a complexity class used to describe certain types of decision problems.
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NP-completeness
In computational complexity theory, an NP-complete decision problem is one belonging to both the NP and the NP-hard complexity classes.
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Operations research
Operations research, or operational research in British usage, is a discipline that deals with the application of advanced analytical methods to help make better decisions.
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Partial function
In mathematics, a partial function from X to Y (written as or) is a function, for some subset X ′ of X.
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Polynomial-time reduction
In computational complexity theory, a polynomial-time reduction is a method of solving one problem by means of a hypothetical subroutine for solving a different problem (that is, a reduction), that uses polynomial time excluding the time within the subroutine.
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Primality test
A primality test is an algorithm for determining whether an input number is prime.
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Recursive set
In computability theory, a set of natural numbers is called recursive, computable or decidable if there is an algorithm which takes a number as input, terminates after a finite amount of time (possibly depending on the given number) and correctly decides whether the number belongs to the set.
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Recursively enumerable set
In computability theory, traditionally called recursion theory, a set S of natural numbers is called recursively enumerable, computably enumerable, semidecidable, provable or Turing-recognizable if.
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Search problem
In computational complexity theory and computability theory, a search problem is a type of computational problem represented by a binary relation.
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String (computer science)
In computer programming, a string is traditionally a sequence of characters, either as a literal constant or as some kind of variable.
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Time complexity
In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.
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Travelling salesman problem
The travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city and returns to the origin city?" It is an NP-hard problem in combinatorial optimization, important in operations research and theoretical computer science.
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Turing degree
In computer science and mathematical logic the Turing degree (named after Alan Turing) or degree of unsolvability of a set of natural numbers measures the level of algorithmic unsolvability of the set.
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Undecidable problem
In computability theory and computational complexity theory, an undecidable problem is a decision problem for which it is known to be impossible to construct a single algorithm that always leads to a correct yes-or-no answer.
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Word problem (mathematics)
In mathematics and computer science, a word problem for a set S with respect to a system of finite encodings of its elements is the algorithmic problem of deciding whether two given representatives represent the same element of the set.
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Yes–no question
In linguistics, a yes–no question, formally known as a polar question or a general question, is a question whose expected answer is either "yes" or "no".
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Zohar Manna
Zohar Manna (born 1939) is a professor of computer science at Stanford University.
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Decidability problems, Decidable problem, Decision problems, Decision procedure, Decision variant, Decision version, Solvable problem, Word problem (computability).
References
[1] https://en.wikipedia.org/wiki/Decision_problem
