6 ms·

As computers are able to evaluate positions faster (and therefore deeper), the "godlike" tactics are dominating over human-style strategy. It used to be that co

by stouset 10y ago

As computers are able to evaluate positions faster (and therefore deeper), the "godlike" tactics are dominating over human-style strategy. It used to be that computers played "computer-like" moves because they didn't understand the position. Now, they play computer-like moves because "understanding" the position isn't as important as just being able to see 25+ moves ahead. In a nutshell, positional play in chess is simply heuristics we humans use to be able to evaluate a position in lieu of being able to calculate deep non-forced lines. Computers do use this to an extent (as you point out, we coded their evaluation functions) but positional play matters less when you see all the outcomes of every possible tactic with 100% accuracy. So computers tend to play reasonably human-like in the openings, but by the time you reach the middle game they'll happily enter lines where their pawn structures are shattered, pieces appear superficially to have little coordination, and where their king safety appears compromised (all things humans rarely intentionally do), all because they've seen that it works out 25+ moves in advance.

1024core 10y ago
> Now, they play computer-like moves because "understanding" the position isn't as important as just being able to see 25+ moves ahead. I don't think you can "see 25+ moves ahead" in Go. The branchout factor is just too big.
- dfan 10y ago
  Well, stouset is talking about chess, but in Go, Monte Carlo Tree Search plays out all the way to the end of the game; it just does so in a much less exhaustive way, for exactly the reason you mention.
- stouset 10y ago
  My comment was in a subthread about computers playing chess in a more human-like manner.
- skj 10y ago
  One of the nice things about Go is that branches rejoin quite a bit, mitigating some of the branching factor concerns.
- rockdoe 10y ago
  You can prune more effectively. Download a program like Leela and let it analyze some positions. You'll get very deep mainlines just like in chess.
kirse 10y ago
they'll happily enter lines where their pawn structures are shattered... Makes you wonder if computers will essentially ruin all the novelty of innovating and discovering new tricks/strategies in age-old games. No more will genius' have their moments of brilliance and improvisation that lead to a stunning victory or upset. No more will commentators debate and regal over phenomenal victories in ages past. With a computer, it's just the optimal play strategy and you were just playing a god who knew the quickest path to terminating your king. When a human runs with non-standard play strategies in almost any game, it's considered brilliant, innovative, game of the century, etc...
- kenshaw 10y ago
  Probably. I think it basically proves that any rule structured game without randomness is solvable.
  - hyeonwho2 10y ago
    Probably still solvable with randomness. Add a few more layers of convolution networks.
  - inimino 10y ago
    Games like go and chess are necessarily solveable by definition, right? If you mean solveable in our lifetimes, by current technology, that's something else entirely, and much less likely. Beating human players in go is like finding a good heuristic for an NP-complete problem. Solving 19*19 go is like proving P!=NP, i.e. we don't even have tools that can approach the problem.
    - malteof 10y ago
      Not sure if this is true for Go. I'm not sure, but it seems to me that at some point a problem becomes "too complex" to solve. I.e. Go has about 2.08168199382×10^170 legal positions [1] and the number of atoms in the observable universe is only up to ~4×10^81. I don't know if there are some theorems, thoughts, philosophies about whether this means it can't be solved, but at least it must be extremely difficult. [1] https://en.wikipedia.org/wiki/Go_and_mathematics#Legal_positions https://en.wikipedia.org/wiki/Go_and_mathematics#Legal_posit...
rockdoe 10y ago
I believe you nailed it yes. Notably, computer games do look reasonably humanlike when they're even,for example when playing another equally strong computer. But once they can outcalculate the opponent this disappears. Compare this to lines that the humans have memorized after deep analysis, like poisoned pawn Najdorf. The play there certainly doesn't look humanlike either.
hyperpape 10y ago
I would not describe the moves dfan is talking about as tactical. Rather, they appear to exhibit a very different positional judgment from what humans use/different strategic aims. What you say sounds plausible, but I do not believe it is backed up by any analysis of the games.
- stouset 10y ago
  Positional play is nothing more than our human attempt to perform short-circuit evaluation of positions by using heuristics that are easier than calculating non-forced lines precisely to 20+ ply. If you imagine a perfect chess-playing computer, it would have no need of any sort of positional evaluation — literally every move it chooses would be based upon the pure tactical outcome of having evaluated every subsequent move in advance. When playing against humans, modern engines can accurately evaluate so much deeper than we can that their play is frequently indistinguishable from the purely tactical play of some such perfect computer (at least, once out of the opening, once the number of "good" moves is constrained a bit allowing computers to evaluate to significantly deeper ply). You say that computers exhibit a different positional judgment, which is true in the "technically correct" sense (their evaluation function is pretty much the literal definition of their positional judgment) but at depths of 25 ply, 30 ply, or even greater, the simple truth is that they are highly willing to enter lines where their king is exposed, they have pawns doubled, they trade away a good bishop and keep their bad bishop, or all of the above (all what we'd consider anti-positional play) just because they can see a concrete outcome (a won piece, a strong attack, etc.) that we can't. So yeah, by some definition they play positionally. But it's really by a definition that's only perhaps useful to other computers and not us humans; to us, it's significantly closer in practice to what we consider highly tactical play.
  - hyperpape 10y ago
    dfan is talking about go. What you're saying is accurate about chess, but go programs aren't the same as chess programs.
ousta 10y ago
if we had unlimited computing power, couldn't we solve any know problem in a way that will ALWAYS outbeat any other way to solve it?

by stouset 10y ago

1024core 10y ago

> Now, they play computer-like moves because "understanding" the position isn't as important as just being able to see 25+ moves ahead. I don't think you can "see 25+ moves ahead" in Go. The branchout factor is just too big.

dfan 10y ago
Well, stouset is talking about chess, but in Go, Monte Carlo Tree Search plays out all the way to the end of the game; it just does so in a much less exhaustive way, for exactly the reason you mention.
stouset 10y ago
My comment was in a subthread about computers playing chess in a more human-like manner.
skj 10y ago
One of the nice things about Go is that branches rejoin quite a bit, mitigating some of the branching factor concerns.
rockdoe 10y ago
You can prune more effectively. Download a program like Leela and let it analyze some positions. You'll get very deep mainlines just like in chess.

kirse 10y ago

they'll happily enter lines where their pawn structures are shattered... Makes you wonder if computers will essentially ruin all the novelty of innovating and discovering new tricks/strategies in age-old games. No more will genius' have their moments of brilliance and improvisation that lead to a stunning victory or upset. No more will commentators debate and regal over phenomenal victories in ages past. With a computer, it's just the optimal play strategy and you were just playing a god who knew the quickest path to terminating your king. When a human runs with non-standard play strategies in almost any game, it's considered brilliant, innovative, game of the century, etc...

kenshaw 10y ago
Probably. I think it basically proves that any rule structured game without randomness is solvable.
- hyeonwho2 10y ago
  Probably still solvable with randomness. Add a few more layers of convolution networks.
- inimino 10y ago
  Games like go and chess are necessarily solveable by definition, right? If you mean solveable in our lifetimes, by current technology, that's something else entirely, and much less likely. Beating human players in go is like finding a good heuristic for an NP-complete problem. Solving 19*19 go is like proving P!=NP, i.e. we don't even have tools that can approach the problem.
  - malteof 10y ago
    Not sure if this is true for Go. I'm not sure, but it seems to me that at some point a problem becomes "too complex" to solve. I.e. Go has about 2.08168199382×10^170 legal positions [1] and the number of atoms in the observable universe is only up to ~4×10^81. I don't know if there are some theorems, thoughts, philosophies about whether this means it can't be solved, but at least it must be extremely difficult. [1] https://en.wikipedia.org/wiki/Go_and_mathematics#Legal_positions https://en.wikipedia.org/wiki/Go_and_mathematics#Legal_posit...

rockdoe 10y ago

I believe you nailed it yes. Notably, computer games do look reasonably humanlike when they're even,for example when playing another equally strong computer. But once they can outcalculate the opponent this disappears. Compare this to lines that the humans have memorized after deep analysis, like poisoned pawn Najdorf. The play there certainly doesn't look humanlike either.

hyperpape 10y ago

I would not describe the moves dfan is talking about as tactical. Rather, they appear to exhibit a very different positional judgment from what humans use/different strategic aims. What you say sounds plausible, but I do not believe it is backed up by any analysis of the games.

stouset 10y ago
Positional play is nothing more than our human attempt to perform short-circuit evaluation of positions by using heuristics that are easier than calculating non-forced lines precisely to 20+ ply. If you imagine a perfect chess-playing computer, it would have no need of any sort of positional evaluation — literally every move it chooses would be based upon the pure tactical outcome of having evaluated every subsequent move in advance. When playing against humans, modern engines can accurately evaluate so much deeper than we can that their play is frequently indistinguishable from the purely tactical play of some such perfect computer (at least, once out of the opening, once the number of "good" moves is constrained a bit allowing computers to evaluate to significantly deeper ply). You say that computers exhibit a different positional judgment, which is true in the "technically correct" sense (their evaluation function is pretty much the literal definition of their positional judgment) but at depths of 25 ply, 30 ply, or even greater, the simple truth is that they are highly willing to enter lines where their king is exposed, they have pawns doubled, they trade away a good bishop and keep their bad bishop, or all of the above (all what we'd consider anti-positional play) just because they can see a concrete outcome (a won piece, a strong attack, etc.) that we can't. So yeah, by some definition they play positionally. But it's really by a definition that's only perhaps useful to other computers and not us humans; to us, it's significantly closer in practice to what we consider highly tactical play.
- hyperpape 10y ago
  dfan is talking about go. What you're saying is accurate about chess, but go programs aren't the same as chess programs.

ousta 10y ago

if we had unlimited computing power, couldn't we solve any know problem in a way that will ALWAYS outbeat any other way to solve it?