Complex Systems: Critical Phenomena

Related lectures (26)

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

Explores the theory of computability, decision problems, complexity classes, and the 'P vs. NP' conundrum.

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

Delves into the theory of computation, covering decidability, complexity, P vs. NP, and reductions.

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

Delves into complexity theory, focusing on the P vs NP problem and the classification of computational problems based on efficiency.

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

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

Explores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.

Explores the knapsack problem and the traveling salesman problem with a focus on optimization algorithms.