Is P = NP?

Now this is my home question. It boils down to the satisfiability problem. Someone suggests the bound is exponential, but with a very small exponent. I think this is a good answer for the observation that SAT is fast for small instances. But we want it to be better, i.e., polynomial. But the boundary between polynomial and exponential is very murky.

Thinking without search. Searching = thinking.

Without a search tree, you can’t prove that something doesn’t work.

Is there a short proof that something doesn’t work? Is there a general strategy to find such proofs?

That amounts to a proof that P ≠ NP.

But it needs to be worked out.

Is there magic, besides logic?

27 thoughts on “Is P = NP?

    1. Define search. Searching is the process of looking at each variable in turn. But the tree can be big or small.

  1. What is thinking? It’s analyzing the formula.

    If this pattern occurs exponential number of times, then it’s already exponent. If, otherwise, it only appears polynomial number of times, then the saving is polynomial. In other words, learning cannot make an exponentially large search space polynomially small.

    1. I’m assuming the running time of discovering a pattern is polynomial. If not, after discovering the pattern, you are already spending too much time, exponential time.

  2. Given a formula and a solution, find the minimum cardinality of a subset which is also a solution. For example, the formula is \(x_1\lor x_2\) and the solution is setting both variables to true. Now a subset is just setting \(x_1\) to true. I think this problem is no easier than SAT itself.

Leave a Reply

Your email address will not be published. Required fields are marked *