Algorithmes: introduction

Related lectures (25)

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

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

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

Covers classical and quantum computational complexity concepts and implications.

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

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

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

Explores challenges in human communication, context importance, compression problems, uncertain functionality, and proof verification.

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.