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."
Tiger Hand!?.
Your hair look like poop, Bob! - Wanker.
We wouldn't want it watching the paper and learning "rock, scissor, human" instead.
Yes, you should. The computer deducted how to play the game on its on. Chess computers like IBM's Deep Blue are programmed how to play chess and beat opponents before playing, and here, the computer doesn't even know how to play; it learns by picking up the sequence of events (the human players say "rock, paper, scissors, who wins or lose") and then forms the ability to play.
Doesn't this seem like A.I.? Rather freaky, to tell you the truth.
Without a proper flamewar, Anonymous was undecided on what shell to run.
What I initially thought of when I saw "Machine Learns Game"
Shall we play a game
Love to. How about rock-paper-scissors.
Wouldn't you prefer a nice game of chess?
Later. Right now lets play rock-paper-scissors
Fine
A strange game. The only way to not look like a dork is not to play.
D6 63 0D 70 89 81 BB 8E 7B 7C 5F 5D 54 EA AB 73
... it only plays at the level of Bart Simpson.
Lisa's brain: Poor predictable Bart. Always takes `rock'.
Bart's brain: Good ol' `rock'. Nuthin' beats that!
Bart: Rock!
Lisa: Paper.
Bart: D'oh!
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
Damn it everybody I know has an awesome sig.
Damn! :-)
and I though you could get this thing to watch cricket and explain the rules to me
If you actually want to understand what they did, some research publications put out by the CogVis lab have better information regarding the technical side of things.
Towards an Architecture for Cognitive Vision Using Qualitative Spatio-temporal Representations and Abduction (Cohn et al, 2003)
Modeling interaction using learnt qualitative spatio-temporal relations and variable length Markov models (Galata et al, 2002)