CS 226 Computability Theorycsetzer/lectures/computability/06/cpslidesdraft… · CS 226 Computability Theory, Lent Term 2007, Sect. 1 1-29. Current State Concurrent and game-theoretic

CS_226 Computability Theoryhttp://www.cs.swan.ac.uk/∼csetzer/lectures/computability/

06/index.html

Course Notes, Lent Term 2007

Anton Setzer(Dept. of Computer Science, Swansea)

http://www.cs.swan.ac.uk/∼csetzer/index.html

Lent Term 2007

CS 226 Computability Theory, Lent Term 2007, Sect. 1 1-1

http://www.cs.swan.ac.uk/~csetzer/lectures/computability/06/index.html

http://www.cs.swan.ac.uk/~csetzer/lectures/computability/06/index.html

http://www.cs.swan.ac.uk/~csetzer/index.html

The Topic of Computability TheoryA

:::::::::::::::

computable::::::::::::

function is a function

f : A → B

such that there is a mechanical procedure forcomputing for every a ∈ A the result f(a) ∈ B.

::::::::::::::::::

Computability:::::::::

theory is the study of computablefunctions.

In computablitity theory we explore the limits of thenotion of computability.


ExamplesDefine exp

:::

: N → N, exp(n) := 2n,

where N = {0, 1, 2, . . .}.exp is computable.However, can we really computeexp(10000000000000000000000000000000000)?

Let String:::::::

be the set of strings of ASCII symbols.

Define a function check::::::

: String → {0, 1} by

check(p) :=

1 if p is a syntactically correctJava program,

0 otherwise.

Is check computable or not?


Remark on VariablesIn this lecture I will often use i, j, k, l, m, n for variablesdenoting natural numbers.

I will often use p, q and some others for variablesdenoting programs.

I will use z for integers.

Other letters might be used as well for variables.

These conventions are not treated very strictly.Especially when running out of letters.


Examples (Cont.)Define a function terminate

:::::::::::: String → {0, 1},

terminate(p) :=

1 if p is a syntactically correctJava program with no input and outputs,which terminates;

0 otherwise.

Is terminate computable?


Examples (Cont.)Define a function issortingfun

::::::::::::::

: String → {0, 1},

issortingfun(p) :=

1 if p is a syntactically correctJava program, which has as inputa list and returns a sorted list,

0 otherwise.

Is issortingfun computable?


ExplanationAssume issortingfun were computable.

Then we can construct (compute) a program whichcomputes terminate as follows:

Assume as input a string p.Check whether it is a syntactically correct Javaprogram with no input and outputs.If no, terminate(p) = 0, so return 0.Otherwise, create a program which is a potentialsorting function as follows:

It takes as input a list l.Then this program runs p.If p has terminated, then it runs a known sortingfunction on l, and returns the result.

CS 226 Computability Theory, Lent Term 2007, Sect. 1 1-6a

ExplanationLet the resulting program (which depends on p) beq(p).If p terminates, then q(p) will be a sorting function, soissortingfun(q(p)) = 1 = terminate(p).If p does not terminate, then q(p) does not terminateon any input, so issortingfun(q(p)) = 0 = terminate(p).Our program returns now issortingfun(q(p)) which isthe result of terminate(p).

So we have obtained by using a program for issortingfun

a program which computes terminate.

But terminate is non-computable, therefore issortingfun

cannot be computable.

CS 226 Computability Theory, Lent Term 2007, Sect. 1 1-6b

Problems in ComputabilityIn order to understand and answer the questions we have to

Give a precise definition of what computable means.That will be a mathematical definition .Such a notion is particularly important for showingthat certain functions are non-computable.

Then provide evidence that the definition of“computable” is the correct one.

That will be a philosophical argument .

Develop methods for proving that certain functions arecomputable or non-computable.


Three AreasThree Areas are involved in computability theory.

Mathematics.Precise definition of computability.Analysis of the concept.

Philosophy.Validation that notions found are the correct ones.

Computer science.Study of relationship between these concepts andcomputing in the real world.


Questions Related to The AboveGiven a function f : A → B, which can be computed,can it be done effectively?(Complexity theory .)

Can the task of deciding a given problem P1 bereduced to deciding another problem P2?(Reducibility theory ).


More Advanced QuestionsThe following is beyond the scope of this module.

Can the notion of computability be extended tocomputations on infinite objects(e.g. streams of data, real numbers,higher typeoperations)?(Higher and abstract computability theory ).

What is the relationship between computing (producingactions, data etc.) and proving.


IdealisationIn computability theory, one usually abstracts fromlimitations on

time and

space.

A problem will be computable, if it can be solved on an ide-

alised computer, even if it the computation would take longer

than the life time of the universe.


History of Computability TheoryGottfried Wilhelmvon Leibnitz (1646 – 1716)

Built a first mechanicalcalculator.

Was thinking about amachine formanipulating symbols inorder to determine truthvalues of mathematicalstatements.

Noticed that this requiresthe definition of a preciseformal language.


History of Computability Theory

David Hilbert(1862 – 1943)

Poses 1900 in hisfamous list “Math-ematical Problems”as 10th problem todecide Diophantineequations.


History of Computability TheoryHilbert (1928)

Poses the “Entscheidungsproblem” (German fordecision problem).


EntscheidungsproblemHilbert refers to a theory developed by him forformalising mathematical proofs.

Assumes that it is complete and sound, i.e. that itshows exactly all “true” formulae.

Hilbert asks, whether there is an algorithm, whichdecides whether a mathematical formula is aconsequence of his theory.

Assuming his theory is complete and sound, such analgorithm would decide the truth of allmathematical formulae.

So we can say that Hilbert asked, whether there is analgorithm which decides the truth of all mathematicalformulae.


EntscheidungsproblemThe question, whether there is an algorithm for decidingthe truth of mathematical formulae is later called the“Entscheidungsproblem” (or “decision problem”).

Entscheidungsproblem became one of the few Germanwords which have entered the English language.


History of Computability TheoryGödel, Kleene, Post, Turing (1930s)Introduce different models of computation and provethat they all define the same class of computablefunctions.



Kurt Gödel (1906 – 1978)Introduced the recursive functionsin his 1933 - 34 Princeton lectures.



Stephen Cole Kleene(1909 – 1994)Probably the most influentialcomputability theoretist up to now.Introduced the partial recursivefunctions.



Emil Post(1897 – 1954)Introduced the Post problems.



Alan Mathison Turing(1912 – 1954)Introduced the Turing machine.Proved the undecidabilityof the Turing-Halting problem.


History of Computability TheoryGödel (1931) proves in his first incompletenesstheorem:

Every reasonable primitive-recursive theory (thetheorem generalises to recursive i.e. computabletheories) is incomplete, i.e. there is a formulas.t. neither the formula nor its negation is provable.Therefore no such theory proves all true formulae.

Recursive functions will be later shown to be thecomputable functions.

Once this is established, it follows that the“Entscheidungsproblem” is unsolvable – an algorithmfor deciding the truth of mathematical formulae wouldgive rise to a complete and sound theory fulfillingGödel’s conditions.


History of Computability TheoryChurch, Turing (1936) postulate that the models ofcomputation established above define exactly the set ofall computable functions (Church-Turing thesis).

Both established undecidable problems and concludedthat the Entscheidungsproblem is unsolvable evenfor a class of very simple formulae .

Church shows the undecidability of equality in theλ-calculus.Turing shows the unsolvability of the halting problem.

It is undecidable whether a Turing machine (andby the Church-Turing thesis equivalently anynon-interactive computer program) eventuallystops.That problem turns out to be the most importantundecidable problem.



Alonzo Church (1903 - 1995)


History of Computability TheoryPost (1944) studies degrees of unsolvability. This is thebirth of degree theory.

In degree theory one devides problems into groups(“

::::::::::

degrees ”) of problems, which are reducible to eachother.

:::::::::::::

Reducible means essentially “relative computable”.

Degrees can be ordered by using reducibility asordering.

The question in degree theory is: what is the structureof degrees?


Degrees

computable

Degree

Reducible to

problems



Yuri VladimirovichMatiyasevich ( ∗ 1947)

Solves 1970 Hilbert’s10th problem nega-tively: The solvabilityof Diophantine equa-tions is undecidable.



Stephen Cook(Toronto)

Cook (1971) intro-duces the complexityclasses P and NPand formulates theproblem, whetherP 6= NP.


Current StateThe problem P 6= NP is still open. Complexity theoryhas become a big research area.

Intensive study of computability on infinite objects (e.g.real numbers, higher type functionals) is carried out(e.g. U. Berger, Jens Blanck and J. Tucker in Swansea).

Computability on inductive and co-inductive data typesis studied.

Research on program synthesis from formal proofs (e.g.U. Berger and M. Seisenberger in Swansea).


Current StateConcurrent and game-theoretic models of computationare developed (e.g. Prof. Moller in Swansea).

Automata theory further developed.

Alternative models of computation are studied(quantum computing, genetic algorithms).

· · ·


Name “Computability Theory”The original name was recursion theory, since themathematical concept claimed to cover exactly thecomputable functions is called “recursive function”.

This name was changed to computability theory duringthe last 10 years.

Many books still have the title “recursion theory”.


Administrative IssuesLecturer :Dr. A. SetzerDept. of Computer ScienceUniversity of Wales SwanseaSingleton ParkSA2 8PPUKRoom: Room 211, Faraday BuildingTel.: (01792) 513368

Fax: (01792) 295651

Email: [email protected]

Home page: http://www.cs.swan.ac.uk/∼csetzer/index.html


mailto:[email protected]

http://www.cs.swan.ac.uk/~csetzer/index.html

Assessment:80% Exam.

20% Coursework.


Course Home PageLocated athttp://www.cs.swan.ac.uk/∼csetzer/lectures/computability/06/index.html

There is an open version,

and a password protected version.

The password is _____________.

Errors in the notes will be corrected on the slides andnoted on the list of errata.

In order to reduce plagarism, coursework and solutionsto coursework will not be made available in electronicform (e.g. on this web site).


Plan for this Module1. Introduction.

2. Encoding of data types into N.

3. The Unlimited Register Machine (URM) andthe halting problem.

4. Turing machines.

5. The primitive recursive functions.

6. The recursive functions and the equivalence theorem.

7. The recursion theorem.

8. Semi computable predicates.


Aims of this ModuleTo become familiar with fundamental models ofcomputation and the relationship between them.

To develop an appreciation for the limits of computationand to learn techniques for recognising unsolvable orunfeasible computational problems.

To understand the historic and philosophicalbackground of computability theory.

To be aware of the impact of the fundamental results ofcomputability theory to areas of computer science suchas software engineering and artificial intelligence.


Aims of this ModuleTo understand the close connection betweencomputability theory and logic.

To be aware of recent concepts and advances incomputability theory.

To learn fundamental proving techniques like inductionand diagonalisation.


LiteratureCutland: Computability. Cambridge University Press,1980.

Main text book.

Thomas A. Sudkamp: Languages and machines.Addison-Wesley 2006.

George S. Boolos, Richard C. Jeffrey, John Burgess:Computability and logic. 4th Ed. Cambridge Univ.Press, 2002

Lewis/Papadimitriou:Elements of the Theory of Computation. Prentice Hall,1981.

Sipser: Introduction to the Theory of Computation.PWS Publishing, 1997.


LiteratureMartin: Introduction to Languages and the Theory ofComputation. 3rd Edition, McGraw Hill, 2003.

Criticized in Amazon Reviews. But several editions.

John E. Hopcroft, R. Motwani and J. Ullman:Introduction to Automata Theory, Languages, andComputation. Addison Wesley, 2nd Ed, 2001.

Excellent book, mainly on automata theory contextfree grammars.But covers Turing machines, decidability questionsas well.


LiteratureVelleman: How To Prove It. Cambridge UniversityPress, 1994.

Book on basic mathematics.Useful if you need to fresh up your mathematicalknowledge.

Griffor (Ed.): Handbook of Computability Theory. NorthHolland, 1999.

Expensive. Postgraduate level.


Documents

CS 226 Computability Theorycsetzer/lectures/computability/06/cpslidesdraft… · CS 226 Computability Theory, Lent Term 2007, Sect. 1 1-29. Current State Concurrent and game-theoretic