Machine Learns Games

heptapod writes "New Scientist is reporting that UK researchers have created a computer that can learn rock, paper, scissors by observing humans. CogVis uses visual information to recognize events and objects in addition to learning by observing."

Comments

Talk about simple

[ReeprFlame]

Doesn't this pretty much invole picking a random action? Rock, Paper, or Scissors. Or at least thats how I always played!

Re:Talk about simple

[TexVex]

RTFA. The computer infers the rules by watching people play.

I do think that according to Game Theory, the perfect strategy is perfect randomness. The game is interesting when people play it because people have a huge amount of trouble actually being random.

Re:Talk about simple

[machine of god]

No, the pinnacle of the game is when you play with someone you know really well, and you have to anticipate them based on what you think their anticipation of what you're going to do is. And of course they're doing the same thing.

My brothers and I can't even play the game because we'll all throw the same sign for half an hour straight.

language?

[rd4tech]

There is a difference in coding between:
a. You go and learn THIS game
b. Learn THAT game and tell me the rules

From the article it can be seen that they are still strugling with 'b'. Still, its a good advance.

Just wondering, can it, learn a human language?

Re:language?

[randallschleufer]

Shouldn't the headline read "Computer learns to play A game", rather than making it sound like this computer is capable of learning the rules of multiple games? I was thinking this computer could learn to play Monopoly or something. Rock Paper Scissors, and it can apparently learn only ONE game. Big whoop.

OOOHHH!!!

[dteichman2]

MORE FUZZY-LOGIC/INFERENCE ENGINE! GO PROLOG-AND-LIKE!

Meh.

Who am I kidding?

Nothing new. Nothing to see here. Even if it is kinda neat.

Profit!

[PingPongBoy]

Logically, a consistent winner of paper scissors rock is a consistent winner of lotteries.

The probability of a fair coin is 0.5, etc. etc. Well, we now have a machine that plays dice to win.

Easy game to learn

[phorm]

Aside from the gesture recognition, it seems like this would bean easy game to learn. The logic is basically

If rock: paper win, scissors lose
If paper: scissors win, rock lose
if scissors: rock win, paper lose

No variable amounts, just straight boolean logic. The next step up might be something like tic-tac-toe... where the machine could start to build some "educated" moves and techniques like blocking, etc.

Really, what is exciting is the spatial recognition. Given the actions, somebody is still telling it what is a win and what is a loss. Without it, learning would be simple enough, given your value and that of the opponent:
Rock: Paper (lose)
Rock: Scissors (win)
Rock: Rock (tie)
Paper: Paper (tie)
Paper: Scissors (lose)
Paper: Rock (win)
Scissors: Paper (win)
Scissors: Scissors (tie)
Scissors: Rock (lose)

No ppl its not that simple....

[carburaettorr]

The system described here is not your average random number generator with a text line output that any high-school kid can write. Let us look at the system as it is designed to perform. If you were the system you would be put into a room with some objects. Only thing that you will know are things of interest. 'Paper with rock drawn on it is important', 'Paper with .......' and so on. You would also know when somebody shouts 'I WON' its a good thing for them. Essentially it has in its knowledge base a tiny number of features which somebody else has guaranteed to be of significance to its task. The first challenge in building such a system is sensor fusion: i.e fusing the available audio and visual data to detect a state or an event of interest (I use the word event in the same sense as a trigger, something that prompts the change in state). The next and the biggest challenge is building the model of the game. Please check out http://www.doc.ic.ac.uk/~shm/ilp.html, for a better description of Inductive logic programming. Seriously; the neatest thing about CogVis is not its ability to play Rock, Paper and Scissors, but its ability to actually go into an environment it has very little knowledge of and then observe, deduce and , not a blackbox model, as in say Neural Networks, but a human understandable model in first order logic

Advanced AI

[antivoid]

Its amazing that this is possible! I read the article and couldn't believe it. Cognitive recognition is one of the first stepping stones to proper artificial intelligence.

Yet when AI reaches the point that it becomes almost human-like, problems are going to form. If the programming of an AI system leads itself to thinks it understands that it is sentient, would it mean that the AI is in fact sentient?

After all, intelligence is intelligence. By any means, an electrical intelligence could be regarded equal, because the only difference between us and "them" would be that we use a chemical and electrical method of processing data, whereas atrifical intelligence-based systems would be using purely electronic methods.

Surely, if input (a video stream coming from an optical sensor, such as a human eye or a digital video camera), and auditory input (ears, or microphone-based) which gets processed (human brain, or CPU) and then output (screen, face, voice, speaker, etc) should not be perceived differently. Humans are data processors (data in, data out in the form of a reaction). Advanced Computer AI would be the same (data in, data out).

Would humans really be that special then?