×

Welcome to the Slashdot Beta site -- learn more here. Use the link in the footer or click here to return to the Classic version of Slashdot.

Thank you!

Before you choose to head back to the Classic look of the site, we'd appreciate it if you share your thoughts on the Beta; your feedback is what drives our ongoing development.

Beta is different and we value you taking the time to try it out. Please take a look at the changes we've made in Beta and  learn more about it. Thanks for reading, and for making the site better!

Neural Net Learns Breakout By Watching The Game On Screen--Then Thrashes Humans

KentuckyFC (1144503) writes | about 4 months ago

0

KentuckyFC (1144503) writes "A curious thing about video games is that computers have never been very good at playing them like humans--by looking at a monitor and judging actions accordingly using. Sure, they're pretty good if they have direct access to the program itself but "hand-to-eye-co-ordination" has never been their thing. But now our superiority in this area is coming to an end. A team of AI specialists in London have created a neural network that learns to play games simply by looking at the RGB output from the console. And they've tested it successfully on a number of games from the legendary Atari 2600 system from the 1980s. The method is relatively straightforward. To simplify the visual part of the problem, the system down-samples the Atari's 128-colour, 210x160 pixel image to create an 84x84 grayscale version. Then it simply practices repeatedly to learn what to do. That's time consuming but fairly simple since at any instant in time during a game, a player can choose from a finite set actions that the game allows: move to the left, move to the right, fire and so on. So the task for any player—human or otherwise—is to choose an action at each point in the game that maximises the eventual score. The researchers say that after learning Atari classics such as Breakout and Pong, the neural net can then thrash expert human players. However, the neural net still struggles to match average human performance in games such as Seaquest, Q*bert and, most important of all, Space Invaders. So there's hope for us yet...just not for very much longer."
Link to Original Source

0 comment

Check for New Comments
Slashdot Account

Need an Account?

Forgot your password?

Don't worry, we never post anything without your permission.

Submission Text Formatting Tips

We support a small subset of HTML, namely these tags:

  • b
  • i
  • p
  • br
  • a
  • ol
  • ul
  • li
  • dl
  • dt
  • dd
  • em
  • strong
  • tt
  • blockquote
  • div
  • quote
  • ecode

"ecode" can be used for code snippets, for example:

<ecode>    while(1) { do_something(); } </ecode>
Sign up for Slashdot Newsletters
Create a Slashdot Account

Loading...