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AI System Invents New Card Games (For Humans)
jtogel writes "This New Scientist article describes our AI system that automatically generates card games. The article contains a description of a playable card game generated by our system. But card games are just the beginning... The card game generator is a part of a larger project to automatise all of game development using artificial intelligence methods — we're also working on level generation for a variety of different games, and on rule generation for simple arcade-like games."
Creating games or levels is pretty simple (well, relatively speaking) in comparison to making them fun. Bu the myriad of bad games out there, I would say that making good games or levels is something not even natural intelligence masters routinely. It is bound to fail trying to do it with AI. Nonetheless a nice research benchmark. But please stop trying to imply real-world usability where there is none. It is unethical and unprofessional.
Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
Shall we play Global Thermonuclear War?
I eat only the real part of complex carbohydrates.
is a 3D printer for sex dolls.
I see MMO expansions someday taking this route to expedite content generation. Players complain there's not enough content? Drag and drop your quest generator with a bit of human tweaking and you're good to go. I'm sure some of the systems in Eve were generated partly through random generation.
Each player gets six cards, except for the player on the dealer's right, who gets seven. .. Two jacks are a "half-fizzbin". If you have a half-fizzbin: a third jack is a "shralk" and results in disqualification. One wants a king and a deuce, except at night ...when one wants a queen and a four. The second card is turned up, except on Tuesdays.
Programmers make me laugh hysterically sometimes. Seriously, when in the history of man has an entire portion of an industry been dedicated to the following two goals:
1) Obsolescence of all current vocational knowledge in their field on 5-15 year scales.
2) The ultimate goal of their work is the removal of their job position from the market (the singularity which can hack in C).
On a tangentally related idea, we're working on a project of machine learning to take games and the rules of play, then derive strategy based on the rules.
Nothing particularly new, except we don't define what winning is, just the rules of the game. No hint is given to what constitutes good play, or even what "playing" is. Although it is a very slow process depending on game complexity (learning can take weeks and sometimes months of processing time), it requires no real programming effort, beause we don't have to know what "good" play is or some series of algorithms; it produces better and better tactics and strategies of play during the learning process, by experimenting with the rules, how to play, and such.
What's cool about this, is that you can watch it teaching itself different strategies and tactics. Some of the "tactics" it creates are many times counter intuitive or plain bizarre, but based on the overall strategies it develops, allows for some really different playing experiences as it doesn't follow human game logic based on experience with "similar" games or "intuition".
I'm a satanic clam.
...when they require three booster packs and a prime card bought off eBay to be competitive!
Lawrence Person (lawrencepersonh@gmailh.com (remove all "h"s to mail)
http://www.lawrenceperson.com/
I see MMO expansions someday taking this route to expedite content generation. Players complain there's not enough content? Drag and drop your quest generator with a bit of human tweaking and you're good to go. I'm sure some of the systems in Eve were generated partly through random generation.
It turns out that procedural generation is conceptually pretty easy; but making it good is much harder. Early videogames(from the era where memory and storage constraints were Serious Business) and demoscene stuff(where the constraints are wholly artificial; but that's the point of the exercise) are pretty much forced to rely on it heavily because they simply didn't have the option of storing canned content.
Today, though, you see games with substantially greater amounts of (not inexpensive) artists and designers thrown at them, and gigabytes of art assets, with hand-tweaking especially evident in places where the player is likely to look closely(eg. generic NPCs will be thrown together from parts, giving the world a varied population without requiring the art people to hand-model 10,000 different 'bandit' characters; but the risk of output that just looks a little off, or hit a few branches of the ugly tree on the way down, means that those critical NPCs that follow you around for half the game had their appearance nailed down precisely). The fact that artists are slow and expensive has created a demand for procedural generation tools, and quite a few exist(I'll just mention SpeedTree, purely because the phrase "SpeedTree for Games has been the gaming industry's premier vegetation solution since 2002" amuses me); but the problem of creating really good environments continues to be vexing enough that titles that can afford it throw a lot of humans at the problem.
It's not too difficult to conceptualize people creating a computer that can design games based upon numerical or statistical elements, such as a deck of 52 cards divided into numbers and sets. Show me a computer than can take a theme (let's say, WWII tactical), create abstract mechanics that reflect playable functionality within that theme (let's say combat rules for historically accurate factions/units/weapons) and then make it fun (Combat Commander anyone?)....well, then I will bow to our new artificial overlords.
So who "owns" the content? Eventually we'll get to a point where AIs are sufficiently robust to create games with minimal human input. Does the human/corporation that owns the AI own its work product via some work-for-hire doctrine? What if the AI can pass the Turing test? Hmm. I think I have an idea for a law journal paper.
Get a piece of the action!
Table-ized A.I.
The latest game they made up (on Friday) was two card draw poker (i.e. hand size is two cards). I worked through the probabilities with them to get the rank of hands correct. (It turns out to be straight flush, pair, straight, flush, high card.)
Quattuor res in hoc mundo sanctae sunt: libri, liberi, libertas et liberalitas.
Here an interesting project description in youtube : Project
So this will be the Architect. Who's working on the Oracle?
The original papers describing the work can be found here:
http://julian.togelius.com/Font2013Towards.pdf
and
http://julian.togelius.com/Font2013A.pdf
Similar evolutionary techniques have been used to generate a number of different types of game content, including Starcraft maps, Super Mario levels, rocks, dungeons, weapons... Here's an overview:
http://julian.togelius.com/Togelius2011Searchbased.pdf
CC.
TaijiQuan (Huang, 5 loosenings)
There is at least one board game that was computer designed: Yavalath. Yavalath was designed algorithmically by Cameron Browne, as described in his PhD thesis "Automatic Generation and Evaluation of Recombination Games". See his publications here:
http://www.cameronius.com/
Roguelike: The Roguelike.
I'll be honest, I fail to see what they're doing that is "new".
Sounds like a 2001/SAW crossover fanfic.
"Would you like to play a game, Dave?"
is pleased with this development. These games must be tested. Let us begin, there is science to be done.
re: We don't define what winning is, how it won, or even what winning is,
.
But usually, the "rules of the game" specifically point out exactly "what winning is". An end goal or an end-state is defined as the desireable outcome, whether it's getting to the end of the squares' sequence in the board game Life or whether it's getting a "higher scoring" hand in poker, the concept of a winning move (or equivalently, a game ending move along with a ranking system that defines who the winner is, e.g. monopoly ends based on money running out for one or all but one player, the rest are ranked by how much money remains).
.
I know I sound pedantic, but if the "system" learns the "rules of the game", then it is given a definition of "what winning is." Have I misunderstood what you're trying to say?
No flying cars yet, but apparently we have Uniblab in alpha.
http://www.thewb.com/shows/the-jetsons/uniblab/d1a360bc-3f5e-478f-86b8-81e8768c823d
If Slashdot were chemistry it would look like this:Cadaverine
Wake me up when an AI invents drinking games
Oh boy! More sameness. Like we didn't have enough of that already - oh but wait, this is progress, it will put game designers out of work if it succeeds. *nods* Corporate entities demand this kind of 'progress for productivity gains'.
Joy.
Pray that AI never learns to sue, today enjoy those nifty games, tomorrow prepare to be sued by AI. Imagine a system like this in the hands of a patent troll.
And for some reason, the computer can always kick your ass at this game, too.
(-1: Post disagrees with my already-settled worldview) is not a valid mod option.
I'm not sure you misunderstood as much as my poor explanation. Although rules of many games specify what winning is, in some cases strategy solutions don't necessarily have a clear definition of winning. Sometimes winning isn't defined as well as treating it as an optimization problem. There are rules of the game, and goals of the game.
As a simple example, take tic-tac-toe. There are rules (you can only put your marker, a X or O in a blank space) which specify what you can do. There are goals that evaluate your play, such as you win with three in a row in various directions, a draw where no one has three in a row, and a loss if your opponent gets three in a row.
There is no other real knowledge of how to play. An expert player will never lose, they will either win or draw based on known strategies that are unbeatable. The basic rules don't define how to do that.
What the learning system does is create strategies. A basic strategy might be, randomly put your X or O in an empty square. You could occassionally win against novice opponents that way. But it would not be an optimal strategy and would regularly lose. Evolve that strategy a bit and you find the system putting its X or O in a proximity which increases its ability to put three in a row. Evolve it a bit more and it can recognize that its opponent is trying to put three in a row and will block it. Evolve it a bit more, and it will block its opponent putting three in a row at the same time putting that block in an advantageous placement to benefit itself to win.
Nothing in the rules specifies this, but is the result of experience or math or research or intuition. The rule is just "The placement rules say you can do 'this'. The measurement of winning is defined as 'that'." The system "learns" from it's mistakes and successes.
Optimization problems are a little different, certainly multiple objective problems. In a more complex "game", you might be trying to optimize solutions for (really we're just talking about a problem domain and a solution space) the stock market, military strategy, chess, TTT, whatever.
The rules of military strategy for an objective can be unique. The rules of the game may be, minimize civilian casualties, you can only use certain type of weapons systems based on political situations, total cost must be under such-and-such, distances must be capable of being reached by units involved, certain enemy units must be captured rather than killed, etc.
Nothing in that tells you HOW to win, it just says, "Here are the rules you must follow, find the best way to do so that comes with the best chance of winning, costs the least, limited friendly-fire situations, etc."
So I guess that's what I mean when I say we don't tell it how to win. We measure winning as what our definition is and how close the strategy solution came to that goal. If it was poker, we would say, "here's the rules of texas hold 'em". The only measurement of winning would be amout of money won. We wouldn't tell it what the hand values were, what were considered good hole cards, or anything else. It would evolve the concept of when to win, bet, bluff, fold, how much to bet at a time, recognizing if it was being bluffed, when do do so based on how many players are in the hand, even what the values of the hands are, etc. At the end a few hundred games, we'd tell it, "Hey you were the best poker playing strategy or you were the worst strategy". That's it. The system evolves 'good' play on its own.
That's what I mean by not telling it how to win. We tell it how it measured against other strategies. It doesn't know what's going on.
I'm a satanic clam.
Great, so given the basic rules of Blackjack it can create a game that appears to have playability almost as good as Blackjack.
Can it create something better than Cribbage or Contract Bridge?
If not then what is the point?