undecidability: what are some determinable problems that cannot be solved in real life (due to time and memory limitations)?

The first line of the Sipser book for the Chapter: "Complexity of time," says that:

Even when a problem is decidable and, therefore, computationally solvable in principle, it may not be solvable in practice if the solution requires an excessive amount of time or memory.

My question is, yes, we have limited space and time, so the above statement makes the entire P and PSPACE concept vague, right? If so, what are these problems? Are such huge contributions acceptable in practice?

(solved) Compact notation for $ k (k + 1) (k + 2) $ …?

Context: diagonals of the Pascal triangle.

My CB only solved about 30% to 35% of catpcha, after a few days of running GSA, how to improve it?


On my first day of GSA execution, CB seems to have a 60% success rate, but after a few days of execution, the success rate was reduced by half, now only a 30% to 35% success rate .

I am using 100 private proxies, and I configured 250 threads in my GSA, the average thread I am running is 100.

I am using SerVerifiedLists.

Hope to hear from you soon. Thank you.

equation resolution: analytical maximization that reduces is not solved

I am working on an interesting problem but stuck in a step where Mathematica fails (no matter from what angle I try to reach).

I am trying to find the maximum symbolic of this convex function (with respect to DY):

PArbNegDY(K0_, Y0_, S0_, DY_, DS_, (Lambda)_) := -DY - (
  K0 (DS + S0) (-1 + (Y0/(DY + Y0))^(1/(Lambda))))/Y0

K0>0 && Y0>0 && S0>0 && DS>-S0 && 0<(Lambda)<=1

enter the description of the image here

So, I was differentiated with respect to DY and now I am trying to solve it:

0 == -1 + (K0 (DS + S0) (Y0/(DY + Y0))^(-1 + 1/(Lambda)))/((DY + Y0)^2 (Lambda))

However, neither solving nor reducing give an answer (reduce executions forever). Any help would be greatly appreciated.

Can the calculation of infinite sums be solved by a computer?

The question is: I give a sum to the computer, as $ sum_ {n = 1} ^ infty frac {1} {n ^ 3} $, the computer is expected to return an elegant solution in a closed way, because the response can be irrational. Has this problem been resolved using a computer? Or has it been proven undecidable? Or is it open?

[SOLVED] Netu.TV support problem! Fraud?? | Proxies123.com

He made a comeback.

I can't contact Netu.tv. He did not respond to what I wrote to the Skype address. Also, the email address did not respond to my writings.

It seems he made my payment on the site, but he didn't pay me. I have added screenshots.

Does anyone use this site? How do I get in touch?

These are not working !!

skype: vladislaviki
mail address: [protected email]


Sorry for the spelling mistakes I wrote using Google Translate.

Resolution of equations: the system can not be solved with the available methods

I can not solve the following system of equations with the Solve in Mathematica command.

Solve[{1[E^(-i (k1 + k2)) (1 + E^(i (k1 + k2))) (E^(2 i k2) x + E^(2 i k1) y)] == 2 (-1 + Cos[k1] + Cos[k2])[E^(i k2) x + E^(i k1) y], 2 ((- (1/2))[E^(-i (k1 - 2 k2)) x + E^(2 i k1 - i k2) y + E^(3 i k2) (x + y)] + (Cos[k1] + Cos[k2])[E^(2 i k2) x + E^(2 i k1) y]) ==
one[(1 + E^(i (k1 + k2))) (E^(i k2) x + E^(I k1) y)]}, {x, y}]

Thanks for any help on the subject.

Theory of complexity: How to prove the problem of the optimization version (whose decision version is NP-complete) can be solved in poly time if p = NP?

I have tried the decision of the version of my problem. $ mathcal {NP} $-to complete. And I know that if I can solve the optimization version in timeout, then I can only compare the minimum (or maximum) obtained with the target value in the decision version. Therefore, the decision version can also be resolved in timeout. Since the decision version is $ mathcal {NP} $-directed, so is the optimization version, that is, the optimization version is $ mathcal {NP} $-hard.

My question is how to test the reverse direction: if the decision version can be resolved in timeout, can the optimization solution also be resolved in timeout?

Thank you in advance for any suggestions!

How can I write a genetic programming algorithm, since the Halting problem can not be solved?

I am learning genetic programming and, to practice, I want to write a simple algorithm that develops a program that solves a simple function (for example, square root). I intend to represent programs as abstract syntax trees.

However, one of the functors is the while loop. Of course, when evaluating the physical state of a tree, I have to evaluate the program: but the problem of detention has no solution. How can I know if a given tree stops? Of course I can not, so what are some practical ways to approach this problem?

Should I make my simple tree language not complete? Or maybe give a wait time to each tree?

Software – Why is the A7R II overheated? It's solved?

The A7R Mark II is known for overheating.

Apparently they released a firmware update but there are reports that it does not work.

It's solved? How did you manage to fix it with a firmware update? How is a mechanical problem supposed to be solved with a quick software update?