Theory of Computation: Countability and Undecidable Problems

Related lectures (23)

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Explores undecidability through recursive languages, Turing machines, and the halting problem.

Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.

Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.

Explores algorithmic complexity, comparing growth rates using Theta notation and characterizing different complexity classes.

Explores the Simon Problem 4, analyzing quantum states and algorithm complexity.

Introduces complexity classes, including P and NP, and explores examples of easy and hard problems.

Explores the theory of computation, emphasizing problems definition, counting, and the limits of algorithmic computation.

Explores critical phenomena in complex systems, including stochastic objects, percolation, and combinatorial optimization.

Explores algorithm correctness, worst-case complexity analysis, and efficiency comparison based on input size.

Examines NP problems, graph coloring, path optimization, and computational complexity distinctions in P and NP classes.