Google DeepMind's AI Beats Humans At Even More Computer Games

An anonymous reader writes: Google DeepMind's learning algorithm has trumped human performance in an even greater range of games from the Atari 2600. The system's performance in classic games for the 80's games console has improved steadily since it was revealed in April last year (video) and a paper released yesterday shows it besting people in 31 titles.

Comments

80's console?

[LordStormes]

The Atari 2600 was released in 1977.

Re:80's console?

[__aaclcg7560]

But the home video game revolution didn't implode until 1983. Hence, 80's console.

Color me shocked

[marcle]

That a computer can beat humans at a computer game.

The real question is, can a computer beat a human at a human game? Chess, yeah. Go, not so much.

Hasn't reverse engineering been around for a while now? If a computer wasn't better and faster at that than a human, that would be the true surprise.

This just in -- maybe it doesn 't require "intelligence" to win most computer games, just good memory and fast reflexes.

Re:Color me shocked

[penguinoid]

Computers have been steadily beating humans at more and more games, "real life" ones or not. Yes, this includes Go. Ironically, humans still beat machines at things that any idiot could do, such as walking or talking or seeing. But even those things are they are getting better and better at (and we aren't), enough to beat us at various surveillance things like recognizing people or license plates.

Humans still beat computers at Calvinball, so there's that.

Re:Color me shocked

[pr0fessor]

I don't want my computer to play classic atari games better than me I want it to make my work easier so I can have more time to play classic atari games, just saying.

Re:Color me shocked

[ShanghaiBill]

The real question is, can a computer beat a human at a human game? Chess, yeah. Go, not so much.

Neural nets are rapidly gaining on old fashioned hand coded algorithms. Here is a Go playing NN, that can beat Gnu Go after only a few days of learning. Progress is rapid, and computers will overtake the best humans at Go within a few years.

Re:Color me shocked

[mspring]

...and no money.

Re:Color me shocked

[Dutch Gun]

Pedantically speaking, computers have been beating humans at videogames since they first appeared in arcades.

It's all in the reflexes

[BlackHawk-666]

Computer with sub-millisecond reaction time and ability to perfectly calculate matrices, vectors and quaternions as well as predict positioning in x amount of seconds beats person. No-one should be surprised.

Re:It's all in the reflexes

[Anonymous Coward]

Deep mind is a neural network based computer. This isn't a competition to aim a laser at a brightly colored balloon. This is a competition to teach a deep neural network strategy and game mechanics. Highly abstract concepts which are not easily encoded in expert systems.

Re:It's all in the reflexes

[ShanghaiBill]

Computer with sub-millisecond reaction time and ability to perfectly calculate matrices ...

This is NOT about computers being able to play well. It is about computers LEARNING to play. The point of TFA, is that DeepMind was simply given the goal of "winning", and then learned on its own how to play the game and maximize the score.

Re:It's all in the reflexes

[dinfinity]

Well, sortof. From TFA:
"However, the system's continued poor performance in Ms Pacman exposes a weakness that DeepMind discussed earlier this year. The limitation stems from the DeepMind system only looking at the last four frames of gameplay, about one fifteenth of a second of the game, to learn what actions secure the best results." (my emphasis)

GP misunderstands the ML aspect of this, but it does come down to reflexes and precision in this specific project. It is nevertheless interesting to investigate which games the net performs badly on and which ones it doesn't.

In a way, this is also a manner of 'ranking' games: the harder it is for such a system to perform well at it, the more cerebral and less primitive/physical it probably is (although I don't want to imply that one type is better than the other)

Let's play global thermonuclear war with it.

[Joe_Dragon]

What side do you want?

1. USA
2. USSR
3. China
4. United Kingdom
5. France
6. India
7. Pakistan
8. North Korea
9. Israel
10. NATO
11. Iran

I hate these stories

[WOOFYGOOFY]

I hate these stories. Games were designed (albeit evolutionarily, through generations of culture) to exploit specific human cognitive limitations in exhaustive search and look ahead, and thereby force us to fall back on things like heuristics and strategies. This makes games unpredictable and interesting.

But computers don't have those limitations. Of course they can out play us at games. They also add faster than we do.

This is all IBM's DeepBlue was, a massive, massive lookahead machine which used a little human-discovered / human programmed rules of thumb to reduce the search space and then human-discovered, human programmed rules of thumb for judging the relative goodness of each move.

The fact that computers are good at beating humans at something specifically designed to make humans perform badly is not an advancement in A.I.

Well, OK it is, but that's not saying much.

Re:I hate these stories

[Moridineas]

But that's not at all the point of this article. The point of this article is that a computer program learned--in a manner SOMEWHAT analogous to human learning--through practicing how to play certain video games without having any game-specific special programming. AI opponents have existed as long as there have been video games (or close to it) and you're right, if that's what this article was about, it would be be boring. Neural net learning by examining visual output--now that's pretty cool.

Re:I hate these stories

[swillden]

In a nutshell, I think it's a disguised way of doing statistics. An iterative, on-analytical way. With neural nets, after it's trained, no one can tell why the neural net functions as it does and no one can tell you when the neural net will do something completely insane.

Just like training a biological brain. And yet, those seem to be somewhat useful.

Re:Rocket League.

[galabar]

Only if it learned on its own.