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AI in Video Games vs. AI in Academia
missingmatterboy writes "Dr. Ian Lane Davis, AI researcher turned game development studio head, talks briefly about the differences between AI used in the game industry and the AI being researched in academic institutions. A short read but you may find it interesting."
This seems a bit much even for Wired. The creatures in these games are following a predefined set of rules, certainly they are a complex set of rules, but the way they "learn" is entirely predetermined (that is, what they learn depends on what they are exposed to, but the formula for converting exposure into knowledge is set by the game designers). I think the fact that the graphics are rendered so realistically makes it easier to make the leap to thinking they are really acting "intelligent."
Who knows what really sets human intelligence apart, is it ability to make rules or nondeterministic memory or whatever, but it seems evident (to me, in my ever-so-humble opinion) that these creatures don't have it.
- adam
This is why I think Asimov's laws regarding intelligent robots/software should be implemented today.
There's a minor problem with that statement, which is that robots aren't nearly bright enough to do any of those things. Not yet, anyway.
For the robot to be able to preserve human life, it must first be able to recognize humans reliably; then it must have a sophisticated situational awareness to understand in what cases a human's life might be in danger, and further, it must be smart enough to understand in what ways that perilous situation might be averted.
For the robot to obey a human's command, it must first be able to accurately interpret that command. Speech and speaker recognition are getting better, but they aren't there yet. And for the robot to again have the situational awareness to know what it is doing and what the results of its actions will be (including whether they endanger a human, as above), it is going to need to be much smarter than anything you can point to today.
Just recognizing humans reliably is a problem. The situational awareness part won't be happening any time soon. Asimov's laws require robots to be a hell of a lot smarter than they are today. By the time robots are smart enough to actually do these things, I'm not sure we'll even care about Asimov's laws (an actual set of ethical values might be a good substitute; hell, it works on humans, somtimes, anyway).
"I don't think all those AI coders out there are thrilled by the idea that their lifes work is used for games
Maybe they're thrilled, maybe they aren't. Aside from conducting interviews with the researchers themselves, we really don't have any way of knowing. That's sort of beside the point, though.
I think the simple fact of the matter is that both applications probably benefit each other, although possibly not in the way most people might think. When I started out programming, a lot of my initial projects were focused on game development. A recurring theme in my thinking was ways to make the computer opponent "smarter", which naturally led me to wonder how I could make the computer learn new tactics and adapt to the human player's actions. As I quickly learned, adaptive systems research is serious stuff.
So, I decided to dig into whatever materials I could get my hands on related to artificial intelligence research and theory. To be honest, I never really got very far, but it remains an interest of mine to this day. I'd be willing to bet some of tomorrow's leading AI researchers are playing video games today. That seems like a pretty good benefit to me.
I guess the key point is this: if a particular application of a certain technology gets people excited about it, and interested in researching it, it's a Good Thing.
One of the main goals of AI in games is to make the computer do things that look like a reasonable person (not necessarily an opponent) would have done them. It doesn't matter if the underlying models are elegant or extensible or whatever. It just needs to make the game fun. But in academic AI, what matters is to get good models, good theory, etc. Academic AI is geared towards the long run. Game AI can be really simple -- for example, you could watch how 100 humans play the game, and try to encode their strategies into the computer player. That kind of "AI" would be uninteresting to academic researchers, but it could make for a fun game.
while i dont disagree that AI will find it difficult to see the big picture, growth between neurons is easy to simulate in a computer program.
repetition simulates growth. just wait until enough repeated events occur to form a solid connection.
metal activity is unguided. there is no reason to guide a self organizing system based on chaos. it just self organises. does anyone "guide" a tornado forming ? the rules are there, let chaos theory do the rest.
It would be impressive if the game's AI coaxes the player to reveal if they actually paid for the game or pirated it, and shut down if pirated.
Table-ized A.I.
I have a hard time agreeing with this. I may not be following your reasoning correctly, but what you seem to be saying is that the programmer has to program in such a way that the AI could never be 'more' than the programmer because the AI would be programmed based on the limits of the programmer's ability.
If we hardcode it's learning ability then, yes, I agree with you in the sense that we will never get anywhere because we have crippled it from the start.
If, however, we create something that has the ability to adjust and even rewrite it's own code and draw conclusions from information that is not directly related ( i.e. infer ) and if we give it a very limited basic set of 'rules' to follow at first, then doesn't the possibility exist that it could eventually 'bootstrap' itself into something more than what we created?
That's ok, Jesus likes me anyway.
This posting quotes from the book to make this point.
Most households were first introduced to computers by video games. It does not surprise me that the first introduction to AI for many people is computer games. I realize that spell checking and grammer checking, a form of AI, may be in many houses too.
Even the military is using game-developed technology for combat simulators.
As someone who does not do games for a living, I find more and more that solutions offered for many games can be more than useful in the 'serious' industry of IT. Way back in the day when 3D was still new to games, the simulator crowd was in high demand for game production. (at least their experience and lessons learned were) Now it seems that more and more gaming solutions could be used for elegant solutions in simulations and distributed information systems (real time). Take the MMOG / persistent world creators... their experience in handling a ton of people with loads of information over the internet, while minimizing lag, cheating (security) and synch problems would be a great boon for MANY systems that are completely unrelated to games. Many in the 'serious' industry scoff at this. Funny thing is, I have done this btw, do an experiment where you present architecture, algorithms and personell that can fulfill the requirements and present it to someone 'up the chain'. They will like it and the ideas presented. now try a month later but add 'game creator/designer/developer' in the personell places and mention that the algorithms are from the 'game world'. You will see a complete 180.
That clearly shows that many put their knee-jerk emotions in front of rational business deciding ability, and should IMO be fired or put in non-decision making capacity positions. Use what works!
It seems to me there is a large disparity in the kind of development between the two different kind of AI investigations. Game AI, although more about the 'result' as stated in the article, has to be based upon the research done in the academia. While it says academia could learn a thing or two by understanding what GAMES are using from AI, they can better focus and optimize and even research better platforms for the games to use (This is just paraphrasing some of what the article might have said, including my own interpretion, if at all accurate).
What I've noticed is, since the human brain knowledge IS 85% speculation, we often use AI strategies to fake knowledge. I mean for FPS bots, they have used paths and nodes to simulate familiarity and some order for the bot, but still that gets too much into a pattern which is not necessarily very human.
I guess my main concern is knowing exactly how far Game AI trails the progress of Academia AI, and when, if ever, the two will progress together.
I'm sick of people asking "When will we see widespread commercial application of AI". AI researchers often quote the so-called "moving frontier" problem, that is, as soon as an AI application becomes useful enough to solve real-world problems, it ceases to be known as AI and looks a whole lot more mundane.
Could it be because it was never AI to begin with? I am sick and tired of the GOFAI (good old fashioned AI) community pasting the AI label on every clever computer application out there so they can cover up their failure to come up with human-level AI. People are not stupid. They can tell the difference between automatic cruise control and HAL. The former is not AI, it's just a clever hack. The latter has real intelligence. Let's face it. The GOFAI research community has failed. They had no clue as to what intelligence is about when they started the field fifty years ago and they have no clue now. We need new blood and new ideas in AI research.
But what is man, if not a self-aware machine?
Um... nearly all of Asimov's robot stories were about situations where following these laws got in the way of doing the Right Thing. Perhaps you should read his work a little more carefully before basing your philosophy of design on it.
Information wants to be anthropomorphized.
character recognition software that reads zipcodes in the post office
natural language translation from french to english
diagnosis and treatment of disease
datamining
texture synthesis
making a helicopter hover still in the air
Robotics is interesting in that it is the holistic (Rod Brooks) view of AI: a robot needs sensory systems, control systems, a planner, etc.
Wow. All the brilliant people at MIT and a dozen other world-class research institutions have been plugging away at this problem, and you managed to figure it all out after a couple of semesters of Lisp. Bravo. Well done. When it's time to accept your Nobel Prize for this remarkable insight, I hope you won't embarrass all the other new laureates by pointing out that all their research was bunk as well. They'd be crushed.
Neurons do not "learn" information in any deep, metaphysical, cogito ergo sum sense. They simply grow and develop based on the inputs they receive.
Is this one of those, "Well, duh" points? Of course it is. You realize this fact as well as I do. But you ignore its implications. There's nothing impossible about creating a software-based "neuron" that can receive inputs, alter itself in response, and then propagate signals to other neurons. Such a construct would be too complex for a programmer to maintain on anything but the highest levels. Therefore, it could not be described merely as a mundane codification of the programmer's intelligence.
The biochemical processes by which intelligence arises in humans, however complicated, are irrelevant in theory. Computing is going on inside your skull, and a Turing machine can properly perform any computation devisable. I believe it's only a matter of time.
Despite what your many many weeks of Lisp programming might have taught you, AI already exists in many forms. They're already doing things thought to be solely the purview of wetware as little as a decade ago. I think the situation within AI right now is analogous to biochemistry back when vitalism was in vogue (18th century, IIRC). Everyone thought that there was something unique and downright supernatural about the chemistry of life. It was even said that no organic molecule would ever be synthesized in a laboratory. Then someone synthesized a really simple molecule--possibly formic acid. Eventually, Watson and Crick came along, and these days nobody in the field would entertain the claim that something in biochemistry can never be understood in principle.
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PhysicsGenius. Heh. Troll handle if I ever heard one.
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