Unraveling the P vs NP Problem in Computer Science

In summary, The P vs NP problem in Computer Science is a millenium problem that asks whether there is a polynomial algorithm to solve all NP problems. It is widely believed that P != NP and that the problem may be solved through boolean algebra. However, it is still undecidable and no one has been able to prove a solution. This problem is considered too advanced for those without a strong background in computer science.
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shamieh
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Didn't know what forum to post this in..There are some brilliant people on this forum, just wanted to know your thoughts on the P vs NP problem in Computer Science? Do you think it will ever be solved? I think P != NP. That being said, I do believe it could be solved but not with normal mathematics. I believe that boolean algebra may be able to solve the problem through LOGIC. As far as statistical formulas creating a Computer AI, I just don't think it's possible. After all, we aren't machines.
 
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  • #2
Of course $\text{P} \neq \text{NP}$ , but I believe this is more or less undecidable.
 
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It seems like it is pretty obvious that P != NP, but how come no one can prove it? Can you give me a example? Like what are the problems people are running into? Or is it too advanced for me to even comprehend? I'm in Calculus II.
 
  • #4
Most problems are more or less undecidable whether in P or NP, so I can't really give you some nontrivial ones. What background have you got in computer science?
 
  • #5
shamieh said:
It seems like it is pretty obvious that P != NP, but how come no one can prove it? Can you give me a example? Like what are the problems people are running into? Or is it too advanced for me to even comprehend? I'm in Calculus II.

One example of a P problem is the inversion of a matrix.

One example of an NP problem is to solve a minesweeper puzzle.

P problems are those which have an algorithm to solve them which takes a number of steps that is a polynomial on the input. In the matrix case, the input are the numbers in the matrix.

NP problems are those which don't have an algorithm to solve them which takes a number of steps that is a polynomial on the input. But this special class of problems also has the property that if you could find a polynomial algorithm to solve one of them, you would solve all of them in polynomial time.

The thing is that you haven't still proved that there is no polynomial algorithm to solve an NP problem. That's the P vs NP millenium problem, which is worth $ 1 000 000.
 

Related to Unraveling the P vs NP Problem in Computer Science

What is P vs NP?

P vs NP is a fundamental problem in computer science that asks whether every problem whose solution can be quickly verified by a computer can also be quickly solved by a computer.

Why is P vs NP important?

Solving the P vs NP problem would have significant implications in many fields, including cryptography, artificial intelligence, and optimization. It could potentially lead to more efficient algorithms and solutions for complex problems.

What is the difference between P and NP?

P stands for "polynomial time," meaning that an algorithm's running time is proportional to the size of the input. NP stands for "nondeterministic polynomial time," meaning that a solution can be verified in polynomial time. The main difference between P and NP is that P problems can be solved efficiently, while NP problems may require exponential time to solve.

Is P vs NP solved?

No, P vs NP is an unsolved problem and is considered one of the most important open questions in computer science. It was first proposed in 1971 and remains unsolved to this day.

What are some real-world examples of P vs NP problems?

Some real-world examples of P vs NP problems include the traveling salesman problem, the knapsack problem, and the Boolean satisfiability problem. These problems are NP-hard, meaning that if they can be solved in polynomial time, then all NP problems can be solved in polynomial time as well.

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