Inmathematics andcomputer science, theEntscheidungsproblem (German for 'decision problem';pronounced[ɛntˈʃaɪ̯dʊŋspʁoˌbleːm]) is a challenge posed byDavid Hilbert andWilhelm Ackermann in 1928.[1] It asks for analgorithm that considers an inputted statement and answers "yes" or "no" according to whether it is universally valid, i.e., valid in everystructure. Such an algorithm was proven to be impossible byAlonzo Church andAlan Turing in 1936.
Bythe completeness theorem of first-order logic, a statement is universally valid if and only if it can be deduced using logical rules and axioms, so theEntscheidungsproblem can also be viewed as asking for an algorithm to decide whether a given statement is provable using therules of logic.
In 1936,Alonzo Church andAlan Turing published independent papers[2] showing that a general solution to theEntscheidungsproblem is impossible, assuming that the intuitive notion of "effectively calculable" is captured by the functions computable by aTuring machine (or equivalently, by those expressible in thelambda calculus). This assumption is now known as theChurch–Turing thesis.
The origin of theEntscheidungsproblem goes back toGottfried Leibniz, who in the seventeenth century, after having constructed a successful mechanicalcalculating machine, dreamt of building a machine that could manipulate symbols in order to determine thetruth values of mathematical statements.[3] He realized that the first step would have to be a cleanformal language, and much of his subsequent work was directed toward that goal. In 1928,David Hilbert andWilhelm Ackermann posed the question in the form outlined above.
In continuation of his "program", Hilbert posed three questions at an international conference in 1928, the third of which became known as "Hilbert'sEntscheidungsproblem".[4] In 1929,Moses Schönfinkel published one paper on special cases of the decision problem, that was prepared byPaul Bernays.[5]
As late as 1930, Hilbert believed that there would be no such thing as an unsolvable problem.[6]
Before the question could be answered, the notion of "algorithm" had to be formally defined. This was done byAlonzo Church in 1935 with the concept of "effective calculability" based on hisλ-calculus, and by Alan Turing the next year with his concept ofTuring machines. Turing immediately recognized that these are equivalentmodels of computation.
A negative answer to theEntscheidungsproblem was then given by Alonzo Church in 1935–36 (Church's theorem) and independently shortly thereafter by Alan Turing in 1936 (Turing's proof). Church proved that there is nocomputable function that decides, for two given λ-calculus expressions, whether they are equivalent or not. He relied heavily on earlier work byStephen Kleene. Turing reduced the question of the existence of an 'algorithm' or 'general method' able to solve theEntscheidungsproblem to the question of the existence of a 'general method' that decides whether any given Turing machine halts or not (thehalting problem). If 'algorithm' is understood as meaning a method that can be represented as a Turing machine, and with the answer to the latter question negative (in general), the question about the existence of an algorithm for theEntscheidungsproblem also must be negative (in general). In his 1936 paper, Turing says: "Corresponding to each computing machine 'it' we construct a formula 'Un(it)' and we show that, if there is a general method for determining whether 'Un(it)' is provable, then there is a general method for determining whether 'it' ever prints 0".
The work of both Church and Turing was heavily influenced byKurt Gödel's earlier work on hisincompleteness theorem, especially by the method of assigning numbers (aGödel numbering) to logical formulas in order to reduce logic to arithmetic.
TheEntscheidungsproblem is related toHilbert's tenth problem, which asks for analgorithm to decide whetherDiophantine equations have a solution. The non-existence of such an algorithm, established by the work ofYuri Matiyasevich,Julia Robinson,Martin Davis, andHilary Putnam, with the final piece of the proof in 1970, also implies a negative answer to theEntscheidungsproblem.
Using thededuction theorem, theEntscheidungsproblem encompasses the more general problem of deciding whether a given first-order sentence is alogical consequence of a given finite set of sentences, but validity in first-order theories with infinitely many axioms cannot be directly reduced to theEntscheidungsproblem. Such more general decision problems are of practical interest. Some first-order theories are algorithmicallydecidable; examples of this includePresburger arithmetic,real closed fields, andstatic type systems of manyprogramming languages. On the other hand, the first-order theory of thenatural numbers with addition and multiplication expressed byPeano's axioms cannot be decided with an algorithm.
By default, the citations in the section are from Pratt-Hartmann (2023).[7]
The classicalEntscheidungsproblem asks, given a first-order formula, whether it is true in all models. The finitary problem asks whether it is true in all finite models.Trakhtenbrot's theorem shows that this is also undecidable.[8][7]
Some notations: means the problem of deciding whether there exists a model for a set of logical formulas. is the same problem, but forfinite models. The-problem for alogical fragment is called decidable if there exists a program that can decide, for each finite set of logical formulas in the fragment, whether or not.
There is a hierarchy of decidabilities. On the top are the undecidable problems. Below it are the decidable problems. Furthermore, the decidable problems can be divided into a complexity hierarchy.
Aristotelian logic considers 4 kinds of sentences: "All p are q", "All p are not q", "Some p is q", "Some p is not q". We can formalize these kinds of sentences as a fragment of first-order logic:where are atomic predicates, and. Given a finite set of Aristotelean logic formulas, it isNLOGSPACE-complete to decide its. It is also NLOGSPACE-complete to decide for a slight extension (Theorem 2.7):Relational logic extends Aristotelean logic by allowing a relational predicate. For example, "Everybody loves somebody" can be written as. Generally, we have 8 kinds of sentences:It isNLOGSPACE-complete to decide its (Theorem 2.15). Relational logic can be extended to 32 kinds of sentences by allowing, but this extension isEXPTIME-complete (Theorem 2.24).
The first-order logic fragment where the only variable names are isNEXPTIME-complete (Theorem 3.18). With, it isco-RE-complete to decide its, andRE-complete to decide (Theorem 3.15), thus undecidable.
Themonadic predicate calculus is the fragment where each formula contains only 1-ary predicates and no function symbols. Its is NEXPTIME-complete (Theorem 3.22).
Any first-order formula has a prenex normal form. For each possible quantifier prefix to the prenex normal form, we have a fragment of first-order logic. For example, theBernays–Schönfinkel class,, is the class of first-order formulas with quantifier prefix, equality and relation symbols, and nofunction symbols.
For example, Turing's 1936 paper (p. 263) observed that since the halting problem for each Turing machine is equivalent to a first-order logical formula of form, the problem is undecidable.
The precise boundaries are known, sharply:
Börger et al. (2001)[11] describes the level of computational complexity for every possible fragment with every possible combination of quantifier prefix, functional arity, predicate arity, and equality/no-equality.
Having practical decision procedures for classes of logical formulas is of considerable interest forprogram verification and circuit verification. Pure Boolean logical formulas are usually decided usingSAT-solving techniques based on theDPLL algorithm.
For more general decision problems of first-order theories, conjunctive formulas overlinear real or rational arithmetic can be decided using thesimplex algorithm, formulas in linear integer arithmetic (Presburger arithmetic) can be decided usingCooper's algorithm orWilliam Pugh'sOmega test. Formulas with negations, conjunctions and disjunctions combine the difficulties of satisfiability testing with that of decision of conjunctions; they are generally decided nowadays usingSMT-solving techniques, which combine SAT-solving with decision procedures for conjunctions and propagation techniques. Real polynomial arithmetic, also known as the theory ofreal closed fields, is decidable; this is theTarski–Seidenberg theorem, which has been implemented in computers by using thecylindrical algebraic decomposition.
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