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Questions and answers designated by tag: Decision Problems

Can every arbitrary problem be expressed as a language?

Sunday, 26 May 2024 by Emmanuel Udofia

In the domain of computational complexity theory, the concept of expressing problems as languages is fundamental. To address this question we need to consider theoretical underpinnings of computation and formal languages. A "language" in computational complexity theory is a set of strings over a finite alphabet. It is a formal construct that can be recognized

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Introduction, Theoretical introduction
Tagged under: Cybersecurity, Decision Problems, Formal Languages, Function Problems, NP-Completeness, Turing Machines

Can a problem be in NP complexity class if there is a non deterministic turing machine that will solve it in polynomial time

Friday, 24 May 2024 by Emmanuel Udofia

The question "Can a problem be in NP complexity class if there is a non-deterministic Turing machine that will solve it in polynomial time?" touches upon fundamental concepts in computational complexity theory. To address this question comprehensively, we must consider the definitions and characteristics of the NP complexity class and the role of non-deterministic Turing

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Complexity, Definition of NP and polynomial verifiability
Tagged under: Computational Complexity, Cybersecurity, Decision Problems, Non-deterministic Turing Machine, NP, Polynomial Time

NP is the class of languages that have polynomial time verifiers

Thursday, 23 May 2024 by Emmanuel Udofia

The class NP, which stands for "nondeterministic polynomial time," is a fundamental concept in computational complexity theory, a subfield of theoretical computer science. To understand NP, one must first grasp the notion of decision problems, which are questions with a yes-or-no answer. A language in this context refers to a set of strings over some

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Complexity, Definition of NP and polynomial verifiability
Tagged under: Computational Complexity Theory, Cybersecurity, Decision Problems, NP, Polynomial Time, Verifier

Is there a contradiction between the definition of NP as a class of decision problems with polynomial-time verifiers and the fact that problems in the class P also have polynomial-time verifiers?

Monday, 27 November 2023 by panosadrianos

The class NP, standing for Non-deterministic Polynomial time, is central to computational complexity theory and encompasses decision problems that have polynomial-time verifiers. A decision problem is one that requires a yes-or-no answer, and a verifier in this context is an algorithm that checks the correctness of a given solution. It’s important to distinguish between solving

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Complexity, Definition of NP and polynomial verifiability
Tagged under: Computational Complexity Theory, Cybersecurity, Decision Problems, Non-deterministic Polynomial Time, Polynomial Time, Verification

What is the definition of the class NP in the context of computational complexity theory?

Thursday, 03 August 2023 by EITCA Academy

The class NP, in the context of computational complexity theory, plays a important role in understanding the complexity of computational problems. NP stands for Nondeterministic Polynomial time, and it is a class of decision problems that can be efficiently verified by a nondeterministic Turing machine in polynomial time. In other words, NP represents the set

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Complexity, Proof that SAT is NP complete, Examination review
Tagged under: Computational Complexity Theory, Cybersecurity, Decision Problems, Nondeterministic Turing Machine, NP, Polynomial Time

What is the difference between NP problems and NP-complete problems?

Thursday, 03 August 2023 by EITCA Academy

In the field of computational complexity theory, specifically in the realm of cybersecurity, understanding the distinction between NP problems and NP-complete problems is of utmost importance. NP (nondeterministic polynomial time) problems and NP-complete problems are both classes of computational problems, but they differ in terms of their complexity and solvability. To begin, let's define what

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Complexity, NP-completeness, Examination review
Tagged under: Computational Complexity Theory, Cybersecurity, Decision Problems, NP Problems, NP-complete Problems

What is the difference between the classes P and NP in computational complexity theory, and how do they relate to the concepts of deciding and verifying membership in languages?

Thursday, 03 August 2023 by EITCA Academy

In computational complexity theory, the classes P and NP play a fundamental role in understanding the efficiency of algorithms and the difficulty of solving computational problems. These classes are defined based on the concept of deciding and verifying membership in languages. The class P consists of all decision problems that can be solved by a

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Complexity, Definition of NP and polynomial verifiability, Examination review
Tagged under: Computational Complexity Theory, Cybersecurity, Decision Problems, Deterministic Turing Machine, P Versus NP Problem, Polynomial Time, Polynomial Verifiability

What is polynomial verifiability and how does it relate to the class NP?

Thursday, 03 August 2023 by EITCA Academy

Polynomial verifiability is a concept in computational complexity theory that plays a important role in the study of the complexity class NP. To understand polynomial verifiability, we must first grasp the definition of NP. NP, which stands for "nondeterministic polynomial time," is a class of decision problems that can be verified in polynomial time. In

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Complexity, Definition of NP and polynomial verifiability, Examination review
Tagged under: Complexity Class, Computational Complexity Theory, Cybersecurity, Decision Problems, NP, Polynomial Verifiability

What is the definition of the complexity class P in computational complexity theory?

Thursday, 03 August 2023 by EITCA Academy

The complexity class P in computational complexity theory is a fundamental concept that characterizes the set of decision problems that can be solved efficiently by a deterministic Turing machine. P stands for "polynomial time" and refers to the class of problems that can be solved in polynomial time. To understand the definition of P, it

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Complexity, Time complexity classes P and NP, Examination review
Tagged under: Computational Complexity Theory, Cybersecurity, Decision Problems, P, Polynomial Time, Turing Machine

Describe the concept of models in computational complexity theory and how they establish a connection between relation symbols in a logical formula and relations in the universe. Provide an example to illustrate this connection.

Thursday, 03 August 2023 by EITCA Academy

In computational complexity theory, the concept of models plays a important role in establishing a connection between relation symbols in a logical formula and relations in the universe. Models provide a formal representation of the relationships and constraints that exist within a given system, allowing us to reason about its properties and behavior. This concept

  • Published in Cybersecurity, EITC/IS/CCTF Computational Complexity Theory Fundamentals, Logic, Truth, meaning, and proof, Examination review
Tagged under: Computational Complexity Theory, Cybersecurity, Decision Problems, Logical Formulas, Models, Relation Symbols
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