
- 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
Russells Paradox in Automata Theory
Russell's Paradox is a famous problem in Set Theory that states a fundamental inconsistency in sets theory in mathematics. This paradox was introduced by the British philosopher and logician Bertrand Russell in 1901. Russell's Paradox challenges the idea that we can define sets in a completely unrestricted way. It shows that certain ways of defining sets lead to contradictions.
In this chapter, we will cover the basics of Russell's Paradox, including its origins, a detailed example for a better understanding.
Understanding Set Builder Notation
To begin with, let us discuss the set builder notation. This notation is commonly used and we are familiar with them. The idea is simple: we define a set by specifying a condition that its elements must satisfy.
A typical set builder notation looks like this:
$$\mathrm{S \:=\: \{x \: \in \: T\: |\: P(x)\: \text{ is satisfied} \}}$$

Here, T is a previously known set, and P(x) is a predicate, or a condition that elements of T must satisfy to be included in S. In other words, S is a subset of T containing all the elements from T that satisfy P(x).
Expanding the Concept of Set Builder Notation
A natural question that arises is whether we can expand this concept. Specifically, can we define sets without starting from a previously known set T? Can we define a set directly from the entire mathematical universe? This idea is known as unrestricted comprehension.
For instance, consider the set:
$$\mathrm{S \:=\: \{x \: \in \: T\: |\: P(x)\: \text{ is satisfied} \}}$$
Here, S includes all elements x from the entire mathematical universe that satisfy the predicate P(x). At first glance, this might seem like a reasonable way to define sets. However, this approach leads to significant problems, as we will see with Russell's Paradox.
Introducing Russells Paradox
Russell's Paradox shows that unrestricted comprehension can lead to a contradiction. The paradox is straightforward but deeply troubling.
It begins by considering a set S defined as follows:
$$\mathrm{S \:=\: {x \:|\: x\: \notin \:x}}$$
In simple terms, S is the set of all sets that are not members of themselves. At first, this definition might seem innocent, but it leads to a contradiction. There are two possibilities to consider:
Possibility 1: S is an element of S
If S is an element of itself, then by the definition of S, it must satisfy the condition x ∉ x. But if S satisfies this condition, then S cannot be an element of itself. This leads to a contradiction because we started by assuming that S is an element of itself.
Possibility 2: S is not an element of S
If S is not an element of itself, then it must satisfy the condition for membership in S, which is x ∉ x. But if S satisfies this condition, then S should be an element of itself, leading to another contradiction.
No matter which possibility we choose, it will be a contradiction. It means the set S, as defined, cannot exist. This is the idea of Russells Paradox, the unrestricted comprehension allows us to define a set that leads to a logical contradiction.
Dealing with the Paradox
Russells Paradox creates a significant problem for set theory and mathematics as a whole. If unrestricted comprehension is allowed, it will be contradiction, which can undermine the entire structure of mathematics. To avoid these contradictions, mathematicians concluded that unrestricted comprehension must be disallowed.
Restricting Comprehension
If we have unrestricted comprehension, there must be restricted comprehension as well. The solution to the problem of unrestricted comprehension is to restrict the comprehension.
Instead of allowing sets to be defined from the entire mathematical universe, we restrict the process to subsets of known sets. It means that we can only define a set S by specifying a condition P(x) that applies to elements of a previously known set T:
$$\mathrm{S \:=\: {x \:\in\: T \:|\: P(x)\: \text{ is satisfied}}}$$
This restriction prevents the paradox from arising because it does not allow the formation of problematic sets like the one in Russells Paradox.
The Issue with the Mathematical Universe
However, even with this restriction, there is still an issue to consider. A famous question in set theory is whether the entire mathematical universe V can be considered a set. If we assume that V is a set, then we can apply restricted comprehension to it. But this leads to a problem similar to Russells Paradox.
Suppose V is a set. According to restricted comprehension, we can define a set T as follows:
$$\mathrm{T = \{x \:\in\: V \:|\: x \:\notin\: x \}}$$
This is essentially the same as Russell's Paradox, and it leads to the same contradiction. If T is an element of T, then T must satisfy x ∉ x, so T cannot be an element of itself. But if T is not an element of T, then T satisfies the condition and must be an element of itself. Again, we get a contradiction.
Consider the mathematical universe is not a Set
This reasoning leads to an important conclusion: the mathematical universe cannot be a set. Even though V consists of all possible sets, it is not itself a set. This is a critical insight in set theory and helps prevent the contradictions that arise from unrestricted comprehension.
Conclusion
In this chapter, we explained the Russells Paradox in detail. We started by understanding the set builder notation and then expanded on the idea by considering unrestricted comprehension.
In Russells Paradox, where we defined a set S that included all sets that are not members of themselves. We saw that this definition led to a contradiction, proving that such a set cannot exist. To resolve this issue, we discussed the need to restrict comprehension to subsets of known sets and concluded that the mathematical universe cannot be considered a set itself.