Theory of Computation - PowerPoint by theoryman

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									Theory of Computation
  What types of things are
How can we demonstrate what
  things are computable?
• Cantor’s Set Theory - contradictions
      • Multiple sizes to infinity.
      • There exists at least one set bigger than the universal
• Hilbert’s rigor
      • Find an algorithm that will generate proofs for all true
• Gödel’s Incompleteness Theorem
      • No such algoritm exists.
      • Even worse, there exist true statements for which no
        proof can ever be found.
      • In any mathematical system there will either be true
        statements that cannot be proven or false statements
        that can.
• The question then becomes, can we at
  least find an algorithm that can find any
  proof that does exist?
  – Church & Kleene and Post found no.
  – Turing developed the “universal algorithm
    machine”, now called the Turing maching.
    This machine also had tasks it could not
   Languages and grammars
• A language is a set of strings.

• A grammar is the set of rules that define
  what strings are valid members of a
                  Rule structure
• Rules consist of three types of symbols:
     • Terminals are symbols that cannot be further expanded.
     • Nonterminals are symbols that are not part of the language’s
       alphabet, but can be expanded into larger substrings
     • , which represents the empty string.
• Assume the alphabet is {a, b}. An example
  grammar might be:
                      S  aSb
                       S  ba
where a and b are terminals and S is a nonterminal.
• Note that rules can be defined recursively.z
          Formal grammars
• A grammar is thus the set of generation rules
  that define the valid strings of the language.
• Any string that can be generated by the
  grammar is a valid string in the language, and
  any string in the language that is valid can be
  generated by the grammar
• The type of grammar used by a language is
  determined by the restrictiveness of the rules.
         Regular grammars
• Regular grammars are ones where the
  the rules have a nonterminal on the left
  and on the right either:
     • The empty string
     • A single terminal
     • A single terminal and a single nonterminal
           » Left regular grammars are ones where the
             nonterminal is to the left of the terminal; in right
             regular grammars, the opposite is true.
 Example regular grammars
     S  aB               S  aB
     B  bB               B  bB
      B                 Ba

What language does   What language does
     this define?         this define?

       ab*                 ab*a
                 State machines
• Designed to allow for the modeling of transitions
  from one state to another.
• Consist of states representing the current state of
  the machine and transitions between those states.
     • Entry Action - the action to perform when the state is entered
     • Exit Action - the action to perform when the state is exited
     • Input Action - an action to perform in a particular state with a a
       particular input (usually involves following a transition)
• Have a start state and an acceptor state
• Transitions define how the machine changes from
  one state to another. They usually define the
  condition(s) under which the machine changes
     • Transition Action - the action to perform when following a
          Finite Automata
• Particular type of state machine that has
  no actions at all. Only states and
 Limits of Regular languages
     and finite automata
• What types of languages can’t FA’s
  accept? In other words, what limits are
  there on the complexity of regular

• FA’s lack memory, so that you can’t
  have one part of a regular language
  dependent on another part.
        Context-free grammars
In CFGs, the rules all take the form:
where N is a single non-terminal and w is some
 finite string of terminals and non-terminals, in any
Whereas in regular languages, nonterminals were
 restricted as to where they could appear in the
 rules, now they can appear anywhere. Hence the
 term context-free.
                       S  aSb
                        S  ab
    CFG example
S  aB         SU
 S  bA         SV
 Aa          U  TaU
 A  aS       U  TaT
A  bAA       V  TbV
 Bb          V  TbT
 B  bS       T  aTbT
B  aBB       T  bTaT
       Pushdown Automata
•   Pushdown automata extend FA’s in one
    very important way. We are now given a
    stack on which we can store information.
    This works like a standard LIFO stack,
    where information gets pushed onto the top
    and popped off the top.
•   This means that we can now choose
    transitions based not just on the input, but
    also based on what’s on the top of the
•   We also now have transition actions
    available to us. We can either push a
    specific element to the top of the stack, or
   Limits on PDAs and CFGs
• Adding memory is nice, but there are
  still significant limits on what a PDA can

• Can a PDA be constructed that can do

• How, or why not?
       The Turing Machine
• Four components:
  – A tape of infinite length, divided into cells,
    which can contain one character of data
  – A head which can read and write in the
    current cell, and which can move the tape
    one cell at a time left or right.
  – A program, which is the set of rules that
    tells us what to do. Our transitions between
    states will now specify the letter we should
    read from the tape, the letter we should
    write to the tape, and the direction we
    should move the tape.

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