Anyway, a few comments on the video:
You’re Doing it Wrong
The first question to the panel was “what do new AI developers do wrong” or something to that effect. DamiÃ¡n set up the idea of two competing mentalities… gameplay vs. realistic behavior. He and John both supported the notion that the game is key and that creating a system just for the sake of creating it can range anywhere from waste of time to downright wrong.
|…create autonomous characters and then let the designers create worlds…
The thing that caught me was Jeff’s response, though (5:48). His comment was that AI teams can’t force designers to be programmers through scripts, etc. That’s not their strength and not their job. While that’s all well and good, it was his next comment that got me cheering. He posited that it is the AI programmers job to create autonomous characters and then let the designers create worlds that let the characters do their thing in.
Obviously, it isn’t a one way street there… the designers job isn’t to show off the AI. However, I like the idea of the designers not having to worry about implementing behavior at all — just asking for it from the AI programmer and putting the result into their world. John’s echo was that it’s nice to build autonomous characters but with overrides for the designers. It isn’t totally autonomous or totally scripted. This sounds like what he told me in his Bioshock experience when I talked to him about it a few years ago.
I happen to agree that the focus needs to be on autonomy first and then specific game cases later. The reason for this is too often the part of the AI that looks “dumb” or “wrong” is when the AI isn’t being told to do anything specific. For example, how often would you see a monster or soldier just standing there? Some of the great breakthroughs in this were from places like Crytek in Far Cry, Crysis, etc. The idea of purposeful-looking idle behaviors was a great boon to believable AI.
The other advantage to creating autonomy first was really fleshed out by Jeff Orkin’s work on F.E.A.R. (Post-Play’em
) No more do designers (or even AI programmers) have to worry about telling an agent exactly what it should do in a situation. By creating an autonomous character, you can simply drop them in a situation and let them figure it out on their own. This can be done with a planner like Jeff did, a utility-based reasoner, or even a very detailed behavior tree. Like John said above, all you need to remember is to provide the override hooks in the system so that a designer can break an AI out of its autonomy and specifically say “do this
” as an exception
rather than hand-specifying each and every action.
What’s in Our Way?
The next question was about “the biggest obstacle” for game AI moving forward. Jeff’s first answer was about authoring tools. This has been rehashed many times over. John expressed his frustration at having to start from scratch all the time (and his jealousy that DamiÃ¡n didn’t have to between Halo 2 and 3).
|…to get your AI reviewed well, you need to invest in great animators.
DamiÃ¡n’s comment was amusing, however. He suggested that to get your AI reviewed well
and have players say “that was good AI”, you need to invest in great animators. This somewhat reflects my comment in the 2009 AI Summit
where I pointed out that AI programmers are in the middle of a pipeline with knowledge representation on one side and animation on the other. It doesn’t do any good to be able to generate 300 subtle behaviors if the art staff can only represent 30 of them.
On the other hand, he reiterated what the other guys said about authoring tools and not having to re-invent the wheel. He supports middleware for the basic tasks like A*, navmesh generation, etc. If we don’t have to spend time duplicating the simple tasks over and over, we can do far more innovation with what we have.
That’s similar to my thought process when I wrote my book, “Behavioral Mathematics for Game AI
“. You won’t see a description of FSMs, A*, or most of the other common AI fare in the book. How many times has that been done already? What I wanted to focus on was how we can make AI work better through things other authors haven’t necessarily covered yet. (Ironically, it was Jeff Orkin who told me “I don’t think anyone has written a book like that. Many people need
to read a book about that. Heck… I’d
read a book about that!” — Thanks Jeff!)
What Makes the Shooter Shot?
The next question (11:45) was about what FPS-specific stuff they have to deal with.
|When Halo 3 came out, they could afford fewer raycasts than Halo 2.
DamiÃ¡n talked about how their challenge was still perception models. They really tried to do very accurate stuff with that in Halo. He pointed out that raycasting is still the “bane” of his existence because it is so expensive still. Despite the processors being faster, geometry is far more complex. Alarming note: When Halo 3 came out, they could actually afford fewer
raycasts than on Halo 2. Now that
sucks! Incidentally, the struggle for efficiency in this area very much relates to DamiÃ¡n’s “blackboard” interview
that I wrote about last week.
Interestingly, Jeff argued the point and suggested that cheating is perfectly OK if it supports the drama of the game. I found this to possibly be in conflict with his approach to making characters autonomous rather than scripted. Autonomy is on the “realistic” end of the spectrum and “scripted” on the other. The same can be said for realistic LOS checks compared to triggered events where the enemy automatically detects the player regardless.
John split the difference with the profound statement, “as long as the player doesn’t think you’re cheating, it’s totally OK.” Brilliant.
AI as the Focus or as a Focusing Tool
|Supporting the overall design of how the game is to be experienced is just as important as the naked math and logic.
In response to a question about what DamiÃ¡n meant about “AI as a game mechanic,” he offered an interesting summation. He said that, from a design standpoint, the AI deciding when to take cover and when to charge is as important as how much a bullet took off your vitality. That is, supporting the overall design of how the game is to be experienced is just as important as the naked math and logic.
He also pointed out that the design of a game character often started out with discussions and examples of how that AI would react to situations. “The player walks into a room and does x and the enemy will do y.” Through those conversations, the “feel” of a type of character would be created and, hopefully, that is what the player’s experience of that type of character would end up being.
In my opinion, a lot of this is accomplished by being able to not only craft behaviors that are specific to a type of enemy (the easy way of differentiation) but also parameterizing personality into those agents so that they pick from common behaviors in different ways. That is, something that all
enemies may do at some point or another but different types of enemies do at different times and with different sets of inputs. I went into this idea quite a bit in my lecture from the 2009 AI Summit (Breaking the Cookie-Cutter: Modeling Individual Personality, Mood, and Emotion in Characters
) where I talked about incorporating personality into game agents.
The Golden Rules of AI (20:30)
Christian started things off by citing the adage, “it’s more important to not look stupid than to look smart.” No big surprise there.
|The player feels good about killing someone if the kill is challenging.
John said that the AI must be “entertaining”. My only problem with this is that different people find different things entertaining. It’s kinda vague. Better to say that the AI must support the design. Both John and Jeff extended this idea by talking about providing a challenge… the player feels good about killing someone if the kill is challenging.
DamiÃ¡n sucked up to my buddy Kevin Dill a little bit my citing a quote that he made in our joint lecture at the GameX Industry Summit, The Art of Game AI: Sculpting Behavior with Data, Formulas, and Finesse
. Kevin said that AI programmers must be an observer of life. I certainly agree with this notion… in fact, for years, my little tag at the end of my industry bios has said, “[Dave] continues to further his education by attending the University of Life. He has no plans to graduate any time soon.” In fact, Chapter 2 of my book is titled “Observing the World”… and Kevin was my tech editor. It should be intuitively obvious, even to the most casual observer, that Kevin stole
that idea from me!
DamiÃ¡n should have cited me
in front of a bunch of game developers! So there!
Anyway, DamiÃ¡n’s point was not only how Kevin and I meant it — observing how people and animals do their thing, but also in being a very detailed and critical observer of your AI. There must be a discipline that scrubs out any little hiccup of animation or behavior before they pile up into a disjointed mess of little hiccups.
Jeff agreed to some extend but related something interesting from the development of F.E.A.R. — he said that most development schedules start by laying out the behavior for each type of character and then, if there is time, you go back and maybe try to get them to work together or with the environment, etc. With F.E.A.R., they started from the beginning with trying to work on the coordinated behaviors. With all the shouting and chaos going on with these guys working against you, you don’t notice the little glitches of the individuals quite as much.
DamiÃ¡n backtracked and qualified his comments… not just hunting down everything that is wrong… but rather everything that is wrong that matters.
Look but Don’t Touch
|If you are fighting for your life, you don’t notice the details as much.
John brought up an interesting helpful hint. He talked about how, by turning on God mode (invulnerability), you can dispense with the fight for survival and really concentrate on how the AI is behaving. If you are fighting for your life, you don’t notice the details as much.
I have to agree. That’s why when I go to places like E3, I would rather stand back and watch other people play so I can observe what’s going on with the AI. (I always fear that demo people at E3 are going to be put off by my refusal to join in.) This is one of the problems I have when I’m playing for my Post-Play’em
articles. I get so caught up in playing that I don’t look for things anymore. One solution is to have a house full of teenagers… that gives you ample time to just sit and watch someone else play games. I recommend it to anyone. (I believe John and DamiÃ¡n have started their respective processes of having teenagers… eventually.)
Emergence… for Good or Evil
|If the AI can have the freedom to accidentally do something cool and fun, it also has the freedom to do something dumb or uninteresting.
In response to a question asking if AI has ever done anything unexpected, DamiÃ¡n spoke about how the sacred quest of emergence isn’t always a good thing. He said that emergent behavior must fall out of the AI having the freedom to do things. If the AI can have the freedom to accidentally do something cool and fun, it also has the freedom to do something dumb or uninteresting. Because of that, emergence has a really high cost in that it can be more of a drag on gameplay than the occasional gem it might produce.
Christian qualified the question a little more by asking if there was a time when the emergent behavior was found well before ship and the team thought it was something to encourage. He cited examples from his own experience. John talked about emergent gameplay that resulted from simple rules-based behavior in Bioshock. You could set a guy on fire, he would run to water, then you could shock the water and kill him. Was it necessary? No. Was it fun for the player to be creative this way? Sure.
To Learn or Not to Learn?
One question that was asked was about using machine learning algos. Christian started off with a gem about how you can do a lot of learning just by keeping track of some stats and not resorting to the “fancier stuff.” For example, keeping track of pitches the player throws in a baseball game doesn’t need a neural network. He then offered that machine learning can, indeed, be used for nifty things like gesture recognition.
|Oh… are you using neural networks?
Jeff admitted that he hates the question that comes up when people find out he does AI in games. They often ask him, “Oh… are you using neural networks?” I think this really hits home with a lot of game AI folks. Unfortunately, even a cursory examination of the AI forums at places like GameDev.net
will show that people still are in love with neural networks. (My quip is that it is because The Terminator claims to be one so it’s real sexy.) Thankfully, the AIGameDev forum
is a little more sane about them although they do come up from time to time. Anyway, Jeff said he has never
used them — and that he’s not even sure he understands them. While he thinks that NNs that are used in-game like in Creatures or Black & White are cool, they are more gimicky and not as useful with the ever-increasing possibility space in today’s games.
I Have a Plan
|It is hard to accommodate the ever-changing goals of the human players.
Jeff acknowledged that the planner revolution that he started has graduated to hierarchical planners to do more complex things like squad interaction. However, one big caveat that he identified was when you incorporate humans into the mix alongside the squad. It is hard to accommodate the ever-changing goals of the human players.
This, of course, brought us back to the idea of conveying intent — one of the nasty little problem spaces of game AI. DamiÃ¡n explained it as a function of interpretation rather than simply one of planning. I agree that this is going to be a major issue for a long time until we can crack the communication barrier such as voice recognition and natural language processing. Until we can tell our AI squad-mates the same thing we can tell our human squad-mates and expect a similar level of understanding, we are possibly at an impasse.
Moving Forward by Standing Still
|As the worlds become more complicated, we have to do so much more work just to do the same thing we did before.
Someone asked the panel what sort of things that they would like to see out of smaller, indie developers that might not be able to be made by the bigger teams. To set the stage, DamiÃ¡n responded with a Doug Church quote from the first AIIDE
conference. Doug said that we have to “move forward by standing still.” As the worlds become more complicated, we have to do so much more work just to do the same thing we did before. (See DamiÃ¡n’s note about the LOS checks in Halo 2 and 3 above.) DamiÃ¡n suggested that the indie space has more opportunities to move forward with this because they aren’t expected to do massive worlds. Instead, they can focus on doing AI-based games.
This is what Matt Shaer’s interview with me in Kill Screen magazine
was going after. With my Airline Traffic Manager
as one of his examples, he spoke specifically about how it is the smaller, dedicated developer who is going after the deeper gameplay rather than the bigger world. I hope this is the case. We have seen a few examples so far… there are likely more to come.
AI on the GPU?
Someone mentioned seeing a demo of improved LOS checks by using the GPU and asked if AI programmers should be pushing that more. John somewhat wittily suggested that AI programmers won’t be using the graphics chips until someone can find a system where a graphics chip isn’t being used at all. DamiÃ¡n was a little more direct in saying that the last people he wanted to work in conjunction with was the graphics programmers. This reminds me of a column I wrote on AIGameDev a few years back, Thou Shalt Not Covet Thy Neighbor’s Silicon
. The graphics guys finally got “their space.” They aren’t letting us have any of it any time soon!
DamiÃ¡n pointed out that most advanced AI needs a lot of memory and access to the game state, etc. Those are things that the GPU isn’t really good at. About the only thing that you could do without those things is perhaps flocking. I agree that there really isn’t a lot we can do with the GPU. He did concede that if ATI wanted to do a raycasting chip (rather than borrowing time from the hated graphics guys) , that would be beautiful… but that’s about it.
Director as Designer?
Someone asked about the possibility of seeing the technology that was behind Left 4 Dead’s “AI Director” being used as a sort of game designer, instead. DamiÃ¡n pointed out that the idea of a “meta-AI” has been around for years in academic AI and that it is now really starting to get traction in the game world. I agree that the customized gameplay experience is a major turning point. I really like the idea of this as it really comes down to a lot of underlying simulation engine stuff. That’s my wheelhouse, really.
Where to Now?
They closed with some commentary on the future of game AI which I will leave to you to listen to. Suffice to say that for years, everyone has been expecting more than we have delivered. I’m not sure that is because we are slacking off of because they have vastly underestimated what we have to do as AI designers and programmers. At least, with all the attention that is being brought to it through the Game AI Conference
puts on, the AI Summit
now being a regular feature at GDC, and other such events, we are going to be moving forward at some speed.
Hang in there…