1. Turing Machines
(At last!)

2. Designing Universal Computational Devices Was Not The Only Contribution from Alan Turing…
Enter the year 1940:
The world is at war
Nazi Germany has succeeded in conquering most of west Europe
Britain is under siege
British supply lines are threaten by German
Germany used the Enigma Code, considered unbreakable
Alan Turing led a group of scientist that broke the enigma code
Enter the year 2006: The National Security Agency (NSA) needs people! (

3. Background Automata accepts regular languages only
For example, {anbn : n = 0, 1, …} is not regular
Pushdown Automata accepts context-free languages only
For example, {anbncn : w  *} is not context-free
We can easily write an algorithm (in C) recognizing if a sequence of characters have the form anbncn or not

4. The Key Question
Is it possible to design a formal model of a computational device that capture the capabilities of any algorithm?
Alan Turing, 1940’s: Yes!

5. Basic Idea Turing decomposed operations in the device as follows:
A pencil will be “observing” symbols from a paper
The pencil can move left and right
Computational steps erase a symbol observed by the pencil and write a new one in its place
The decision about which symbol should be written and which will be observed next depend on:
The current symbol being observed
The “state of mind” of the device
This device is called a Turing Machine

6. Turing Machine Looks Similar to Finite Automata
Common:
A “state of mind” sounds like the collection of states
A “pencil” sounds like the pointer for the next word
Main differences:
Turing machines can write on the “paper”
Turing machines can backup and read symbols again
This turns out to be a major difference!

7. In Turing’s Own Words
... which can be made to do the work of any special-purpose machine, that is to say to carry out any piece of computing, if a tape bearing suitable "instructions" is inserted into it.

8. Expressivity of Turing Machines (TMs)
TMs can simulate any data structure
TMs can simulate major components of imperative languages: sequence, branching and loop
TMs can control branching and loops
Several extensions have been attempted: adding multiple heads (pencils), tapes, non-determinism, etc. But we can show that TMs can simulate each of these extensions

9. Church-Turing Thesis
Every computer algorithm can be implemented as a Turing machine
Therefore, C, C++, Prolog, Lisp, Small talk, and Java programs can be simulated in Turing machines
Definition: a programming language is Turing-complete if it is equivalent to a Turing machine.

10. Informal Description Control head a1 a2 … Tape cell The head:
Reads the symbol from the cell it is pointing to, and
Either:
Writes a new symbol in the cell, or
Moves one cell to the left or right

11. Informal Description (II)
New cells can be added to the right of the tape as needed (similar to RAM memory)
These new cells contain the blank symbol, 
The tape is bounded to the left

12. Preliminaries to Formal Description
 denotes the alphabet of characters in language as usual.
 denotes the set of symbols that can be written on tape
It contains  and all symbols in 
Transitions can be described by (Case I):
((s,a),(q,b,))
If the machine is in state s and the current cell has an a then jump to state q and write b in the current cell and moves head to right

13. Preliminaries to Formal Description (II)
Transitions can be described by (Case II):
((s,a),(q,b,))
If the machine is in state s and the current cell has an a then jump to state q and write b in the current cell and moves head to left

14. Formal Definition
Definition. A Turing machine is a 7-tuple (Q, , , , q0, qaccept, qreject),
where:
Q is a set of states
 is a set of symbols (the alphabet)
 is a set of symbols that can be written in tape,    and   
q0  Q is the initial state
qaccept is the accepting state
qreject is the rejecting state, qreject  qaccept

15. Formal Definition (II)
 is a collection of transitions defined by the function:
: (Q  {qaccept, qreject })    Q    {, }

16. My First Turing Machine
Construct a Turing machine such that:
input: a substring over the alphabet  ={a,b}, the substring contains at least 1 character b
the header is pointing to the first cell in tape
When the Turing machine halts, the header must be pointing to the first occurrence of b in the input a b a  a b a 

17. Discussion: Are you sure that such a simple model can simulate my C++ program for computing the Minimum Spanning Tree?

18. The “Eraser” TM
Construct a Turing machine that receives as input a substring of a’s and replace each a for a blank space,  a a a     

19. Configuration for Turing Machines
The current state, q
The symbol pointed by the head, h
The string left of the head, LS
The string right of the head, RS
(q,h,LS,RS)

20. Configuration for Turing Machines (2)
Instead of writing: (q,h,LS,RS), we write:LSqhRS
If q = qaccept, then LSqhRS is called an accepting configuration
If q = qreject, then LSqhRS is called a rejecting configuration
Examples:
- Initial configuration with 3 a’s for the eraser TM:
eq0aaa
- Accepting configuration starting with eq0aaa:
qaccept

21. Computation in Turing Machines
A configuration C1 = LS1q1h1RS1 yields a configuration C2 = LS2h2q2RS2 in one step, written C1 C2, if: 
There is a transition: (q1, h1) = (q2,h2,)
The other case is analogous for (q1, h1) = (q2,h2,)
C yields C’, written C * C’: 
There is a sequence of configurations in one step:
C C C1 … C’
Example: eq0aaa yields eq0

22. Two Forms of Computability
Definition. A word w is accepted by a Turing machine M if M yields an accepting configuration starting from the configuration eq0w
Definition. The language L(M) recognized by a Turing machine M:
L(M) = {w | w accepted by M}
Definition. A language L is Turing-recognizable if there is a Turing machine that recognizes L
Definition. A language L is decidable if there is a Turing machine M such that:
L(M) = L
For any word w L, M yields a rejecting configuration starting from the configuration eq0w

23. Constructing Complex Turing Machines
Idea:
Use a modular approach similar to the one use to construct complex programs
Example (programming):
Given two nn matrixes A and B to compute ABT we:
Construct a procedure to compute BT, transverse(B,C)
Construct a procedure to multiply two matrices, multiply(B,C,D)
Call transverse(B,C) and then multiply(A,C,D). D contains the answer

24. Graphical Conventions
We will use a convention similar to a flow chart to indicate how to put together Turing machines (TMs).
Convention. Let A and B be 2 TMs, and a be a character in  then: A a B A;
if a then B
Means that:
If A halts in a configuration of the form w1qacceptaw2 where w1or w2 are any words
Then B starts with the configuration w1q0aw2

25. Graphical Conventions (2)M a a M;
If a then A
else B A B
Means that:
If M halts in a configuration of the form w1qacceptaw2, then A starts with the configuration w1q0aw2
If M halts in a configuration of the form w1 qacceptw2 with   a, then B starts with the configuration w1q0w2

26. Graphical Conventions (3)
while (not a) do A a A
Means that:
If the initial configuration has the form w1q0w2, then A starts with this configuration if   a, where s is the initial state in A
If A halts in a configuration of the form w1qacceptw2 with   a, then A starts with the configuration w1q0w2

27. Basic Turing Machines a
Denotes “write a on the current cell” (a is a character in ) 
Denotes “move to the right of the current cell” (the book uses “R” instead of “”) 
Denotes “move to the left of the current cell” (the book uses “L” instead of “”)

28. Other Simple Turing Machines
What it does a
“if current cell has an a, then replace it with a b” b a 
“if current cell has a character a different than , then move once to the right and write that a”

29. The  Turing Machine –  –   What it does?
Move to the right until if finds 

30. The  Turing Machine
Draw diagram for    –

31.  and  – –  –
Move to the left until the first non-blank space cell is found   –
Move to the right until the first non-blank space cell is found 

32. The Conventions 2 simple rules: Rule # 1: Rule # 2: R
“move to the right until you find “ R
“move to the right until you find a symbol other than “
Note: first check. Then move (think of a “while”)
“Never forget Rule # 1”
(Mr Miogi, The Karate Kid)

33. Example: Deciding the language (ab)* a b
“yes” a b  a b a a
“no”