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In computational complexity theory, a complexity class is a set of problems of related complexity. A typical complexity class has a definition of the form:
For example, the class NP is the set of decision problems that can be solved by a non-deterministic Turing machine in polynomial time, while the class PSPACE is the set of decision problems that can be solved by a deterministic Turing machine in polynomial space. Some complexity classes are sets of function problems, such as FP. Many complexity classes can be characterized in terms of the mathematical logic needed to express them; see descriptive complexity. The Blum axioms can be used to define complexity classes without referring to a concrete computational model. Relationships between complexity classesThe following table shows some of the classes of problems (or languages, or grammars) that are considered in complexity theory. If class X is a strict subset of Y, then X is shown below Y, with a dark line connecting them. If X is a subset, but it is unknown whether they are equal sets, then the line is lighter and is dotted. Technically, the breakdown into decidable and undecidable pertains more to the study of computability theory but is useful for putting the complexity classes in perspective. See alsoFurther reading
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