Mostrando entradas con la etiqueta Video Game. Mostrar todas las entradas
Mostrando entradas con la etiqueta Video Game. Mostrar todas las entradas

domingo, 21 de junio de 2015

Automated Super Mario World gameplay through machine learning


Seth Bling made a bot — MarI/O — that automatically learns how to play Super Mario World. It's based on research by Kenneth O. Stanley and Risto Miikkulainen from 2002 that uses neural networks that evolve with a genetic algorithm. MarI/O starts out really dumb, just standing in place, but after enough simulations it get smart enough to navigate the world.



Code available here and the paper from Stanley and Mikkulainen is here.

See also: the genetic algorithm walkers.


ORIGINAL: Flowing Data

martes, 3 de marzo de 2015

Google Builds An AI That Can Learn And Master Video Games


Google has built an artificial intelligence system that can learn – and become amazing at – video games all on its own, given no commands but a simple instruction to play titles. The project, detailed by Bloomberg, is the result of research from the London-based DeepMind AI startup Google acquired in a deal last year, and involves 49 games from the Atari 2600 that likely provided the first video game experience for many of those reading this.

While this is an amazing announcement for so many reasons, the most impressive part might be that the AI not only matched wits with human players in most cases, but actually went above and beyond the best scores of expert meat-based players in 29 of the 49 games it learned, and bested existing computer based players in a whopping 43.

Google and DeepMind aren’t looking to just put their initials atop the best score screens of arcades everywhere with this project – the long-term goal is to create the building blocks for optimal problem solving given a set of criteria, which is obviously useful in any place Google might hope to use AI in the future, including in self-driving cars. Google is calling this the “first time anyone has built a single learning system that can learn directly from experience,” according to Bloomberg, which has potential in a virtually limitless number of applications.

It’s still an early step, however, and Google expects it’ll be decades before it achieves its goal of building general-purpose machines that have their own intelligence and can respond to a range of situations. Still, it’s a system that doesn’t require the kind of arduous training and hand-holding to learn what it’s supposed to do, which is a big leap even from things like IBM’s Watson super computer.

Next up for the arcade AI is mastering the Doom-era 3D virtual worlds, which should help the AI edge closer to mastering similar tasks in the real world, like driving a car. And there’s one more detail here that may keep you up at night: Google trained the AI to get better at the Atari games it mastered using a virtual take on operant conditioning – ‘rewarding’ the computer for successful behavior the way you might a dog.

ORIGINAL: Tech Crunch

martes, 21 de mayo de 2013

The Earth Hack

ORIGINAL: Marblar


In a generation's time they will wonder how we could be so short-sighted and stupid.

Having the world's brightest minds just creating more complicated simulations and academic papers isn't working, we can all see that.

But in a generation's time they won't have this problem.

The brightest people just got a bit brighter with a really simple idea. It's time to start channeling the latent genius worldwide to collaboratively attack the biggest challenges in climate change head-on. Better still, it's in the form of a game.

Not in a generation's time, but today. It's time for TheEarthHack.



Countries taking part in TheEarthHack

Who's making TheEarthHack happen?





? Revealed in 6 days

? Revealed in 13 days
Impatient? Contact us now