P vs NP Guessing and process of elimination

In summary, the conversation discusses the complexity of Sudoku puzzles and their relation to the P vs NP problem in computer science. While Sudoku puzzles can often be solved by eliminating possible numbers, harder puzzles require thinking ahead and making guesses. The P vs NP problem considers whether these types of problems can be solved without guessing or using an oracle tape.
  • #1
Anders Serup Poulsen
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If we suppose there is an algorithm for P vs NP, would it have to be able to find solutions where we now use trial and error? In harder Sudokus, for example, there are times when you have two or more possible numbers and need to guess whereafter you work the rest of the numbers through to see if what you guessed is right. There is a distinction between problems where the solution is given by the process of elimination and problems where you have to guess. Does P vs NP concern the former only or also the latter? An answer would be very much appreciated!
 
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  • #2
Its not that you have to guess but rather you must consider possible numbers in multiple blank squares in the sudoku before determining the correct number for the square of interest. This is like selecting a move in chess where you must forecast a few moves ahead to decide if the current move is a good choice.

https://en.wikipedia.org/wiki/Mathematics_of_Sudoku

and this paper describes the general class of sudoku puzzles as NP-complete:

http://www-imai.is.s.u-tokyo.ac.jp/~yato/data2/SIGAL87-2.pdf

and a discussion here at Math Stack Exchange:

https://math.stackexchange.com/questions/445540/is-the-sudoku-puzzle-np-complete
 
  • #3
Okay, "guessing" is not the right word then. In a lot of sudokus, you can find the solution by eliminating possible numbers but in the harder ones you get stuck and need to think several steps ahead like you said. Does the P vs NP problem contain both "types"? I feel like the problem gets much more complicated when you need to think steps ahead than when you don't.

From what I understand chess is in a more complex class of problems than sudoku.
 
  • #4
Thank you for your reply (and sorry for my lack of vocabulary - English is not my first language)
 
  • #5
##NP## means that a guess is possible. ##N## stands for non-deterministic. If I remember correctly, one can model it by a Turing machine with an oracle tape. Important is, that a guessed or whatever achieved solution can be verified in polynomial time ##P \subseteq NP##. ##NP## completeness of Sudoku means, that if we had a polynomial time algorithm for any Sudoku riddle, we could also decide all other problems in ##NP## in polynomial time, because there is a polynomial time translation from Sudoku into all other problems, e.g. the traveling salesman problem or the Boolean satisfiability problem. The general question behind ##NP=P##, that is ##NP \subseteq P##, is, whether there is a way to solve such problems without a guess, or an oracle tape.
 
  • #6
Anders Serup Poulsen said:
If we suppose there is an algorithm for P vs NP, would it have to be able to find solutions where we now use trial and error? In harder Sudokus, for example, there are times when you have two or more possible numbers and need to guess whereafter you work the rest of the numbers through to see if what you guessed is right. There is a distinction between problems where the solution is given by the process of elimination and problems where you have to guess. Does P vs NP concern the former only or also the latter? An answer would be very much appreciated!
Are you referring to "proper puzzles" , i.e., those having a unique solution, or to general ones?
 
  • #7
Those with just one solution.
 

What is the P vs NP problem?

The P vs NP problem is one of the most famous unsolved problems in computer science and mathematics. It asks whether every problem whose solution can be quickly verified by a computer can also be quickly solved by a computer. In simpler terms, it asks if there is an efficient way to solve difficult problems.

What is the difference between P and NP?

P is the set of problems that can be solved in polynomial time, meaning the time it takes to solve the problem is proportional to a polynomial function of the input size. NP is the set of problems that can be verified in polynomial time, meaning the time it takes to check if a given solution is correct is proportional to a polynomial function of the input size. The P vs NP problem is essentially asking if P = NP.

How does guessing and process of elimination relate to P vs NP?

One approach to solving difficult problems is to use guessing and process of elimination. This means trying out different solutions and eliminating the ones that do not work until the correct solution is found. However, the P vs NP problem asks if there is a more efficient way to solve these problems, without having to rely on guessing and process of elimination.

Why is the P vs NP problem important?

The P vs NP problem has implications for many fields, including computer science, mathematics, and cryptography. If it is proven that P = NP, it would mean that many currently difficult problems could be solved efficiently, leading to advancements in technology and science. On the other hand, if it is proven that P ≠ NP, it would mean that there are problems that are fundamentally difficult to solve, which would have important consequences for encryption and data security.

Has the P vs NP problem been solved?

No, the P vs NP problem remains unsolved and is considered one of the most challenging problems in computer science. Many attempts have been made to prove or disprove it, but so far no definitive answer has been found. It is currently classified as one of the seven Millennium Prize Problems and is a topic of ongoing research and debate in the scientific community.

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