Theory of Computability: Solvability and Complexity

Related lectures (25)

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Explores algorithm complexity, big-O notation, induction, recursion, and analysis of running times, covering NP problems and complexity classes.

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

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Explores the theory of computation, undecidable problems, complexity measurement, and the P complexity class.

Covers complexity classes, tractable problems, the class NP, NP-complete problems, and summarizes the concept of tractable problems.

Covers complexity classes, effect on computer time, tractable problems, class NP, and NP-complete problems.

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

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

Covers the basics of algorithms, problem-solving, and efficient resolution methods.

Delves into oracles, certificates, and the NP complexity class, raising the fundamental P versus NP question.