Computability theory

Author(s):  
Daniele Mundici ◽  
Wilfried Sieg

The effective calculability of number-theoretic functions such as addition and multiplication has always been recognized, and for that judgment a rigorous notion of ‘computable function’ is not required. A sharp mathematical concept was defined only in the twentieth century, when issues including the decision problem for predicate logic required a precise delimitation of functions that can be viewed as effectively calculable. Predicate logic emerged from Frege’s fundamental ‘Begriffsschrift’ (1879) as an expressive formal language and was described with mathematical precision by Hilbert in lectures given during the winter of 1917–18. The logical calculus Frege had also developed allowed proofs to proceed as computations in accordance with a fixed set of rules; in principle, according to Gödel, the rules could be applied ‘by someone who knew nothing about mathematics, or by a machine’. Hilbert grasped the potential of this mechanical aspect and formulated the decision problem for predicate logic as follows: ‘The Entscheidungsproblem [decision problem] is solved if one knows a procedure that permits the decision concerning the validity, respectively, satisfiability of a given logical expression by a finite number of operations.’ Some, for example, von Neumann (1927), believed that the inherent freedom of mathematical thought provided a sufficient reason to expect a negative solution to the problem. But how could a proof of undecidability be given? The unsolvability results of other mathematical problems had always been established relative to a determinate class of admissible operations, for example, the impossibility of doubling the cube relative to ruler and compass constructions. A negative solution to the decision problem obviously required the characterization of ‘effectively calculable functions’. For two other important issues a characterization of that informal notion was also needed, namely, the general formulation of the incompleteness theorems and the effective unsolvability of mathematical problems (for example, of Hilbert’s tenth problem). The first task of computability theory was thus to answer the question ‘What is a precise notion of "effectively calculable function"?’. Many different answers invariably characterized the same class of number-theoretic functions: the partial recursive ones. Today recursiveness or, equivalently, Turing computability is considered to be the precise mathematical counterpart to ‘effective calculability’. Relative to these notions undecidability results have been established, in particular, the undecidability of the decision problem for predicate logic. The notions are idealized in the sense that no time or space limitations are imposed on the calculations; the concept of ‘feasibility’ is crucial in computer science when trying to capture the subclass of recursive functions whose values can actually be determined.

Author(s):  
Giuseppe Primiero

This chapter illustrates the basic tools of computability theory, essential to the formulation of the decision problem and the definition of the notion of computable function.


1966 ◽  
Vol 31 (3) ◽  
pp. 409-414 ◽  
Author(s):  
Kenneth R. Brown ◽  
Hao Wang
Keyword(s):  

In this paper, a simple inductive characterization of the ordinal numbers is stated and developed. The characterization forms the basis for a set of axioms for ordinal theory and also for several short explicit definitions of the ordinals. The axioms are shown to be sufficient for ordinal theory, and, subject to suitable existence assumptions, each of the definitions is shown to imply the axioms.The present results apply to the familiar von Neumann version of the ordinals, but the methods used are easily adapted to other versions.


Author(s):  
Sarah Sophie Pohl ◽  
Christian Richter

Abstract The old Chinese puzzle tangram gives rise to serious mathematical problems when one asks for all tangram figures that satisfy particular geometric properties. All 13 convex tangram figures are known since 1942. They include the only triangular and all six quadrangular tangram figures. The families of all n-gonal tangram figures with $$n \ge 6$$ n ≥ 6 are either infinite or empty. Here we characterize all 53 pentagonal tangram figures, including 51 non-convex pentagons and 31 pentagons whose vertices are not contained in the same orthogonal lattice.


2017 ◽  
Vol 82 (2) ◽  
pp. 420-452
Author(s):  
KRISHNENDU CHATTERJEE ◽  
NIR PITERMAN

AbstractWe generalize winning conditions in two-player games by adding a structural acceptance condition called obligations. Obligations are orthogonal to the linear winning conditions that define whether a play is winning. Obligations are a declaration that player 0 can achieve a certain value from a configuration. If the obligation is met, the value of that configuration for player 0 is 1.We define the value in such games and show that obligation games are determined. For Markov chains with Borel objectives and obligations, and finite turn-based stochastic parity games with obligations we give an alternative and simpler characterization of the value function. Based on this simpler definition we show that the decision problem of winning finite turn-based stochastic parity games with obligations is in NP∩co-NP. We also show that obligation games provide a game framework for reasoning about p-automata.


2016 ◽  
Vol 494 ◽  
pp. 236-244 ◽  
Author(s):  
Noemí DeCastro-García ◽  
Miguel V. Carriegos ◽  
Ángel Luis Muñoz Castañeda

Author(s):  
Subrata Dasgupta

Let us rewind the historical tape to 1945, the year in which John von Neumann wrote his celebrated report on the EDVAC (see Chapter 9 ). That same year, George Polya (1887–1985), a professor of mathematics at Stanford University and, like von Neumann, a Hungarian-American, published a slender book bearing the title How to Solve It. Polya’s aim in writing this book was to demonstrate how mathematical problems are really solved. The book focused on the kinds of reasoning that go into making discoveries in mathematics—not just “great” discoveries by “great” mathematicians, but the kind a high school mathematics student might make in solving back-of-the-chapter problems. Polya pointed out that, although a mathematical subject such as Euclidean geometry might seem a rigorous, systematic, deductive science, it is also experimental or inductive. By this he meant that solving mathematical problems involves the same kinds of mental strategies—trial and error, informed guesswork, analogizing, divide and conquer— that attend the empirical or “inductive” sciences. Mathematical problem solving, Polya insisted, involves the use of heuristics—an Anglicization of the Greek heurisko —meaning, to find. Heuristics, as an adjective, means “serving to discover.” We are oft en forced to deploy heuristic reasoning when we have no other options. Heuristic reasoning would not be necessary if we have algorithms to solve our problems; heuristics are summoned in the absence of algorithms. And so we seek analogies between the problem at hand and other, more familiar, situations and use the analogy as a guide to solve our problem, or we split a problem into simpler subproblems in the hope this makes the overall task easier, or we summon experience to bear on the problem and apply actions we had taken before with the reasonable expectation that it may help solve the problem, or we apply rules of thumb that have worked before. The point of heuristics, however, is that they offer promises of solution to certain kinds of problems but there are no guarantees of success. As Polya said, heuristic thinking is never considered as final, but rather is provisional or plausible.


Author(s):  
Rohit Parikh

Church’s theorem, published in 1936, states that the set of valid formulas of first-order logic is not effectively decidable: there is no method or algorithm for deciding which formulas of first-order logic are valid. Church’s paper exhibited an undecidable combinatorial problem P and showed that P was representable in first-order logic. If first-order logic were decidable, P would also be decidable. Since P is undecidable, first-order logic must also be undecidable. Church’s theorem is a negative solution to the decision problem (Entscheidungsproblem), the problem of finding a method for deciding whether a given formula of first-order logic is valid, or satisfiable, or neither. The great contribution of Church (and, independently, Turing) was not merely to prove that there is no method but also to propose a mathematical definition of the notion of ‘effectively solvable problem’, that is, a problem solvable by means of a method or algorithm.


2019 ◽  
Vol 27 (3) ◽  
pp. 381-439
Author(s):  
Walter Dean

Abstract Computational complexity theory is a subfield of computer science originating in computability theory and the study of algorithms for solving practical mathematical problems. Amongst its aims is classifying problems by their degree of difficulty — i.e., how hard they are to solve computationally. This paper highlights the significance of complexity theory relative to questions traditionally asked by philosophers of mathematics while also attempting to isolate some new ones — e.g., about the notion of feasibility in mathematics, the $\mathbf{P} \neq \mathbf{NP}$ problem and why it has proven hard to resolve, and the role of non-classical modes of computation and proof.


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