Theory of Computation: Problems Definition and Counting (Denumerability)

Related lectures (21)

Page 1 of 3

Explores countability and undecidable problems in the theory of computation.

Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Explores the existence of functions that cannot be computed, illustrated by famous paradoxes and the concept of undecidable problems.

Explores counting infinite sets and decision problems, showcasing the limits of computation in solving certain undecidable problems.

Covers strings, countable sets, cardinality, and the concept of countability, exploring the countability of various sets and Cantor diagonalization.

Explores finite transition systems, propositional logic, truth interpretation, satisfiability, and boolean function representation with circuits.

Covers recursively enumerable languages, Turing machines, and the construction of undecidable languages.

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Introduces numbers and booleans in Python, covering numeric types, arithmetic operations, logical operations, and comparisons.