Computational Complexity Theory
Computational Complexity Theory is a branch of computer science that studies the resources required for solving computational problems. It aims to classify problems based on their inherent difficulty and to understand the limitations of algorithms and computing machines. The theory focuses on the analysis of the time and space complexity of algorithms, as well as the classification of problems into complexity classes such as P, NP, and NP-complete. It also deals with the study of the relationships between different complexity classes and the development of techniques for proving lower bounds on the complexity of problems. Computational Complexity Theory has important applications in cryptography, optimization, artificial intelligence, and many other fields.
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