
- Automata Theory - Applications
- Automata Terminology
- Basics of String in Automata
- Set Theory for Automata
- Finite Sets and Infinite Sets
- Algebraic Operations on Sets
- Relations Sets in Automata Theory
- Graph and Tree in Automata Theory
- Transition Table in Automata
- What is Queue Automata?
- Compound Finite Automata
- Complementation Process in DFA
- Closure Properties in Automata
- Concatenation Process in DFA
- Language and Grammars
- Language and Grammar
- Grammars in Theory of Computation
- Language Generated by a Grammar
- Chomsky Classification of Grammars
- Context-Sensitive Languages
- Finite Automata
- What is Finite Automata?
- Finite Automata Types
- Applications of Finite Automata
- Limitations of Finite Automata
- Two-way Deterministic Finite Automata
- Deterministic Finite Automaton (DFA)
- Non-deterministic Finite Automaton (NFA)
- NDFA to DFA Conversion
- Equivalence of NFA and DFA
- Dead State in Finite Automata
- Minimization of DFA
- Automata Moore Machine
- Automata Mealy Machine
- Moore vs Mealy Machines
- Moore to Mealy Machine
- Mealy to Moore Machine
- Myhill–Nerode Theorem
- Mealy Machine for 1’s Complement
- Finite Automata Exercises
- Complement of DFA
- Regular Expressions
- Regular Expression in Automata
- Regular Expression Identities
- Applications of Regular Expression
- Regular Expressions vs Regular Grammar
- Kleene Closure in Automata
- Arden’s Theorem in Automata
- Convert Regular Expression to Finite Automata
- Conversion of Regular Expression to DFA
- Equivalence of Two Finite Automata
- Equivalence of Two Regular Expressions
- Convert Regular Expression to Regular Grammar
- Convert Regular Grammar to Finite Automata
- Pumping Lemma in Theory of Computation
- Pumping Lemma for Regular Grammar
- Pumping Lemma for Regular Expression
- Pumping Lemma for Regular Languages
- Applications of Pumping Lemma
- Closure Properties of Regular Set
- Closure Properties of Regular Language
- Decision Problems for Regular Languages
- Decision Problems for Automata and Grammars
- Conversion of Epsilon-NFA to DFA
- Regular Sets in Theory of Computation
- Context-Free Grammars
- Context-Free Grammars (CFG)
- Derivation Tree
- Parse Tree
- Ambiguity in Context-Free Grammar
- CFG vs Regular Grammar
- Applications of Context-Free Grammar
- Left Recursion and Left Factoring
- Closure Properties of Context Free Languages
- Simplifying Context Free Grammars
- Removal of Useless Symbols in CFG
- Removal Unit Production in CFG
- Removal of Null Productions in CFG
- Linear Grammar
- Chomsky Normal Form (CNF)
- Greibach Normal Form (GNF)
- Pumping Lemma for Context-Free Grammars
- Decision Problems of CFG
- Pushdown Automata
- Pushdown Automata (PDA)
- Pushdown Automata Acceptance
- Deterministic Pushdown Automata
- Non-deterministic Pushdown Automata
- Construction of PDA from CFG
- CFG Equivalent to PDA Conversion
- Pushdown Automata Graphical Notation
- Pushdown Automata and Parsing
- Two-stack Pushdown Automata
- Turing Machines
- Basics of Turing Machine (TM)
- Representation of Turing Machine
- Examples of Turing Machine
- Turing Machine Accepted Languages
- Variations of Turing Machine
- Multi-tape Turing Machine
- Multi-head Turing Machine
- Multitrack Turing Machine
- Non-Deterministic Turing Machine
- Semi-Infinite Tape Turing Machine
- K-dimensional Turing Machine
- Enumerator Turing Machine
- Universal Turing Machine
- Restricted Turing Machine
- Convert Regular Expression to Turing Machine
- Two-stack PDA and Turing Machine
- Turing Machine as Integer Function
- Post–Turing Machine
- Turing Machine for Addition
- Turing Machine for Copying Data
- Turing Machine as Comparator
- Turing Machine for Multiplication
- Turing Machine for Subtraction
- Modifications to Standard Turing Machine
- Linear-Bounded Automata (LBA)
- Church's Thesis for Turing Machine
- Recursively Enumerable Language
- Computability & Undecidability
- Turing Language Decidability
- Undecidable Languages
- Turing Machine and Grammar
- Kuroda Normal Form
- Converting Grammar to Kuroda Normal Form
- Decidability
- Undecidability
- Reducibility
- Halting Problem
- Turing Machine Halting Problem
- Rice's Theorem in Theory of Computation
- Post’s Correspondence Problem (PCP)
- Types of Functions
- Recursive Functions
- Injective Functions
- Surjective Function
- Bijective Function
- Partial Recursive Function
- Total Recursive Function
- Primitive Recursive Function
- μ Recursive Function
- Ackermann’s Function
- Russell’s Paradox
- Gödel Numbering
- Recursive Enumerations
- Kleene's Theorem
- Kleene's Recursion Theorem
- Advanced Concepts
- Matrix Grammars
- Probabilistic Finite Automata
- Cellular Automata
- Reduction of CFG
- Reduction Theorem
- Regular expression to ∈-NFA
- Quotient Operation
- Parikh’s Theorem
- Ladner’s Theorem
Godel Numbering in Automata Theory
In meta-mathematics and logics, Gdel Numbering is an interesting concept. It was developed by Austrian mathematician Kurt Gdel. This concept plays a huge role in Gdel's incompleteness theorems. In this chapter, we will see the basics of Gdel Numbering, explain how it works, and walk through a couple of examples for a better understanding.
Gdel Numbering
Gdel Numbering provides a method of encoding mathematical expressions as numbers. This technique allows us to transform abstract mathematical concepts into arithmetic notations, which makes it possible to apply number theory to questions of logic.
Gdel developed this method as part of his proof that there are true statements in mathematics that cannot be proven within a given formal system. This idea was a groundbreaking result that challenged the previous efforts to create a complete and consistent set of mathematical axioms.
Understanding the Basics
Let us first understand a few basic concepts in logic and mathematics −
- Calculus − In this context, calculus refers to a system of signs that do not have any inherent meaning on their own. These signs are used to construct formulas.
- Variables − Variables can be either sentential (like p, q, r) or numerical (like x, y, z). Sentential variables can be replaced by statements, while numerical variables can be replaced by numbers.
- Connectives − These are logical operators like "not" (~), "and" (), "or" (∨), and "if...then" (⊃).
- Quantifiers − Quantifiers such as "for all" (∀) and "there exists" (∃) are used to generalize statements.
Let us understand how Gdel Numbering is constructed.
Constructing Gdel Numbers
Gdels approach starts with the idea of assigning a unique number to every symbol, the formula, and the proof within a logical system. This unique number is known as a Gdel Number.
To achieve this, Gdel chose a system of symbols that includes all cardinal numbers and arithmetic operations like addition and multiplication. The idea is that each symbol and formula in the system can be translated into a unique number.
Basic Symbols of Gdel Numbers
Here is how Gdel assigned numbers to some basic symbols −
Symbol | Gdel Number |
---|---|
~ | 1 |
∨ | 2 |
⊃ | 3 |
∃ | 4 |
= | 5 |
0 | 6 |
s | 7 |
( | 8 |
) | 9 |
+ | 10 |
× | 11 |
For example, the symbol "~" (which means "not") is assigned the Gdel Number 1, and the symbol "V" (which means "or") is assigned the Gdel Number 2.
Defining Variables
Next, we have to define variables using Gdel Numbers. There are two types of variables −
- Numerical variables (x, y, z) and
- Sentential variables (p, q, r).
- Predicate variables are also used, representing statements like "is prime."
Let us see how these variables might be assigned Gdel Numbers −
Variable Type | Gdel Number | Possible Substitution |
---|---|---|
Numerical Variable | x | 13 |
Numerical Variable | y | 17 |
Sentential Variable | p | 132 |
Predicate Variable | P | 133 |
Example of Gdel Numbering
Let us see an example to see how Gdel Numbering is applied. Consider the expression (∃x) (x = sy), which means "there exists an x such that x is the immediate successor of y."
The Gdel Numbers for each symbol in this expression are −
- ( : 8
- ∃ : 4
- x : 13
- ) : 9
- = : 5
- s : 7
- y : 17
Now, instead of representing this formula as a sequence of numbers, Gdel proposed converting it into a single unique number. This is done by raising the first n prime numbers to the power of the corresponding Gdel number and then multiplying the results together.
The calculation for our example would look like this −
$$\mathrm{2^8 \times 3^4 \times 5^13 \times 7^9 \times 11^5 \times 13^7 \times 17^17}$$
This huge number, which we can m, is guaranteed to be unique due to the Fundamental Theorem of Arithmetic (which states that every number has a unique prime factorization).
Extending Gdel Numbering to Proofs
Gdel's method also allows us to assign unique numbers to entire proofs, which are sequences of formulas. If we have two formulas with Gdel Numbers m and n, the Gdel Number for the proof that links them would be calculated as −
$$\mathrm{k = 2^m \times 3^n}$$
This method shows that every symbol, formula, and proof in the system can be uniquely identified by a Gdel Number.
Decrypting Gdel Numbers
We have seen how we can convert the expression to Gdel Numbers, let us see the decoding now. We can work backward to determine what expression it represents. For example, if we are given the number 243,000,000, which has the prime factorization 26 × 35 × 56, we can decode it to find the original expression it represents. In this case, it corresponds to the expression 0=0.
Arithmetization of Meta-Mathematics
This idea was unique and has several applications. Gdel's next step was to express statements about mathematical formulas as arithmetic relationships between their corresponding Gdel Numbers.
For example, if a formulas Gdel Number is a, and we want to know what the first symbol in the expression is, we can examine the prime factorization of a. The exponent of the first prime in the factorization reveals which symbol it is.
Conclusion
In this chapter, we have covered the basics of Gdel Numbering. This is a system that encodes mathematical expressions as unique numbers. We explored the fundamentals of this concept, how Gdel Numbers are assigned, with an example to how it works.
We also explained how Gdel's method can be extended to proofs and used to decipher expressions from their Gdel Numbers.