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An AI created by a Microsoft-owned machine/deep learning team has completely conquered Ms. Pac-Man, achieving a perfect score:
At long last, the perfect score for arcade classic Ms. Pac-Man has been achieved, though not by a human. Maluuba — a deep learning team acquired by Microsoft in January — has created an AI system that's learned how to reach the game's maximum point value of 999,900 on Atari 2600, using a unique combination of reinforcement learning with a divide-and-conquer method.
AI researchers have a documented penchant for using video games to test machine learning; they better mimic real-world chaos in a controlled environment versus more static games like chess. In 2015, Google's DeepMind AI was able to learn how to master 49 Atari games using reinforcement learning, which provides positive or negative feedback each time the AI attempts to solve a problem.
Though AI has conquered a wealth of retro games, Ms. Pac-Man has remained elusive for years, due to the game's intentional lack of predictability. Turns out it's a toughie for humans as well. Many have tried to reach Ms. Pac-Man's top score, only coming as close as 266,330 on the Atari 2600 version. The game's elusive 999,900 number though, has so far only been achieved by mortals via cheats.
(Score: 0) by Anonymous Coward on Thursday June 15 2017, @10:40PM (1 child)
Actually, I would like to hear this. I know a bit about randomness from my introductory studies in AI, and some amateur interest. What is this rant abuot?
(Score: 2) by KGIII on Friday June 16 2017, @12:31AM
I posted a good portion of it, in a few different replies.
For starters, we call as sorts of things random that really aren't necessarily random. And, worse, we don't actually have the computational ability to determine if they're random. What they are, however, is "random enough." You can find some pretty good sources of random based on things like cosmic rays. There are some who will say it's true random, there are others who'd disagree.
(Hecht, Jeff, and Torrey, Lee; "Scientists Find Sources of Cosmic Rays," New Scientist, 99:764, 1983.)
I guess, if I had to put myself into a category, I'd say I'm an undecided determinist.
If you can get your hands on a copy of What is Random by Ed Beltrami, that is a good start. A decent uni library should have a copy. If you absolutely can't find a copy, let me know. I think I have an extra. I think...
You might be able to find some works from one Avi Wigderson, as well. They tend to work more along the lines of pseudorandomness and computation. There's still a bunch of good information and I believe they're still in academia so their work should be easier to find. As for a specific work, I'm just gonna suggest diving in at whatever seems interesting.
"So long and thanks for all the fish."