This time, I invoke Chris Hecker and his speculation on whether or not we will find “the Photoshop of AI”. To quote from the column:
In his lecture entitled Structure vs. Style, he pointed out that the cusp in graphics presentation technology was when the atomic building block was settled on – that of the the texture-mapped triangle. [However], there is a major component of the game experience that hasn’t yet found the spark for it’s Big Bang of development such as the one that occurred in the graphics universe. Game AI has yet to find that “one thing” that their world can be reduced to. And, as such, there can be no “Photoshop for AI”, as Chris put it. Yet.
If you are an AI developer or even just interested in game AI, please wander over and read the whole column… and then weigh in on the subject. What is that single core component that we need in order for AI to make the leap to the next level? Does it even exist?
Ted Vessenes wrote a nifty little post on his blog where he compared designing and programming AI to being a parent. Here’s the opening paragraph:
“Writing artificial intelligence is a lot like being a parent. It requires an unbelievable amount of work. There are utterly frustrating times where your children (or bots) do completely stupid things and you just can’t figure out what they were thinking. And there are other times they act brilliantly, and all the effort feels satisfying and well spent.”
I have to agree with a lot of the points he makes in his post. I would like to take the analogy one step farther.
I’ve occasionally made the point about both parenting and AI that your job is to not define what your progeny should do but convey an understanding of why. If, as a parent, you tell your child not to run in the street, they will hopefully carry that lesson into the future. However, they may not apply that same edict to driveways, parking lots or any other places where they could get plowed over by a car. This is analogous to the scripted AI methodology. However, if you explain the why of the situation – i.e. “be careful anywhere that cars are moving because the driver may not see you in time to stop and you could get badly hurt” – then the simple rule can be applied to any situation where there are cars (or even car-like objects). This, of course, maps over to rule-based systems or even planning systems.
However, going back to Ted’s point, it is an interesting similarity to put all those rules into place and hope that your little bots realize the appropriate situations in which to use them. I actually wrote a column about this scary process on my weekly column over at AIGameDev.
Anyway, if you are an AI developer, I hope that you are blessed with many children who all grow up to be accomplished in their chosen lives (or deaths).
This time, I touch on the concept of Chaos Theory and how the AI buzzword of emergent behavior is actually cut from the same cloth. They are both entirely deterministic in that they are composed of a finite set of distinct rules – and yet their strength (and weakness) is in that they look complex… even to the point of looking random at times.
But is this good or bad? To pull a brief quote from the column:
So our agent-based models are really an implementation of Chaos Theory. That is, they are both complex systems that result entirely deterministically from relatively simple models. However, as Jurassic Park so elegantly portrayed for us, even deterministic models can spin wildly out of control. There are plenty of examples of very simple systems whose results can vary widely – almost looking “broken” simply because of the interaction of those simple rules.
And that is the rub. That is the beast that waits below the surface to reach up and wrap it’s combinatorial tentacles around our placid simulation and drag it down into the abyss of scathing reviews. And we never know if and when it will strike. Perhaps the name “Chaos Theory”, although not an appropriate term for describing the system itself, was an appropriate one after all for describing the potential results of that system.
Read the whole column over at AIGameDev.com. And please, these are discussion columns. If you have a comment, by all means leave it!
The title of this column, “Does This Mistake Make Your AI Look Smarter?“, is a tongue in cheek way of pointing out that there are questions about our AI that are really difficult for us to answer honestly. Skipping over the amusing analogy at the beginning of the column, this is what the crux of it is:
…since the inception of game AI, we have been trying to have our agents make better decisions, not worse ones. We have been trying to eliminate stupid behaviors, not encourage them. We have been striving for more realism, not less… but wait a minute… Isn’t this where we might be lying to ourselves? And do we really want to hear the answer if it means we have been wrong all along?
In this week’s column, “Thinking Beyond Single Frame Decisions“, I wanted to provoke some thought about why it is that AI programmers have often painted themselves in the corner mentality that AI decisions need to be made in a single frame – 20ms or so – even if we have to cut corners on accuracy or depth in order to do so.
As AI programmers, we are forced (or force ourselves) up against the invisible wall of framerates. Our agents must live their lives in 20 millisecond slices -perceiving, pondering, planning and performing must all be arranged in little easily-digestible bites. What’s more, they share their cramped temporal quarters with dozens, scores, or even hundreds of other cohorts – all clamoring for the leftovers that the art department has discarded… and all working under the same 20ms edict. If you can’t decide what to do in 20ms, it isn’t worth doing.
If you can spare the clock cycles, head on over to Alex Champandard’s excellent community, AIGameDev.com. Remember to tap the RSS feed to the discussion column and his many other blog feeds! While you are there, spawn another helper thread and jump into the AI forums as well. (Forum registration is required but is quick and painless. If you are an AI programmer, you’ve dealt with more traumatic experiences than that!)
I have to admit, I am really enjoying writing for Alex and his site. I’m honored that he asked me to be a part of his team.
If you haven’t already done so, make sure you subscribe to IA on AI to keep up with the latest news and notes on game AI!
Is it possible for an AI to be both “good” and “fun”?
Take the time to jump on over and read it… and then comment either here or in the excellent AI forums there. (Forum registration may be required to comment… but then if you are an AI programmer, you need to be involved over there anyway!)
AIGameDev.com has a great, in-depth interview with Dmitriy Iassenev, the AI mastermind for S.T.A.L.K.E.R. The game has a very extensive A-life system that lends a lot of depth to the game. In Dmitriy’s words:
The gist of the A-life is that the characters in the game live their own lives and exist all the time, not only when they are in the player’s field of view. It eventually runs counter to the customary optimization processes used in games development (why perform operations invisible to the player?). Thus, such a scheme is reasonable to be used only when you know exactly what you want to have in the end. We had the game designers’ requirements to have the characters that could not only live inside a certain level, but move between the levels, memorizing the information they obtained during their existence. Consequently, we have decided that each character should come with only one logical essence regardless of the level he is at; whereas we could try to implement that with various tricks involved.
Read more of this very detailed interview over at AIGameDev.com – the place for the killer AI stuff on killer games!
Just in time for the Super Bowl, here’s an interesting analysis on AIGameDev. It covers some of the very unique challenges that are endemic to the AI of football and even sports games in general.
One very interesting link from that article is a pdf file walking through the evolution of the AI in the Madden series since it started in (get this) 1986. That does point to an advantage that the Madden franchise has in its development… they get to iterate every single year. That means they can build upon their past code, get feedback from a massive user base, and tweak to their hearts content. I very much recommend reading through the document.
Another gem from over at what is rapidly becoming our sister-site, AIGameDev.com – this is the result of a discussion that started a few weeks amongst the site regulars.
Of the top 5, I’m the most excited about an increase in sandbox games and emergent behaviors. Really, I see these two as almost interlinked. Sandbox games not only allow emergent behavior to proliferate – they almost require it to do so in order to keep immersion.
Likewise, interagent cooperation was another of the top 5 on the list. Again, this is something that I see as related to emergent behavior. If you leave your cooperation loosely defined rather than pre-scripted, you will see a lot of emergent behavior as a result.
I hope to get more a feel about this very topic at the GDC roundtables and lectures next month. That is always a great way to take the pulse of the industry. Anyway, good stuff on the list.
I hate glomming on to a blog chain, but I’m going to link to AIGameDev’s article on an article (which may very well be about an article.) The title is Watching Level Designers Use Scripts to Disable Your Autonomous AI: Priceless – which just about covers it. Alex does a nice job of not just reporting on it, but explaining the mindset and even the things to watch out for.
Regular readers of my other blog, Post-Play’em will know that I talked about the idea of scripts over-riding AI behaviors in Call of Duty 2 in a post entitled Call of Duty 2: Omniscience and Invulnerability. Specifically, this was in reference to one of the behaviors mentioned in the other article where an AI agent takes on a temporary god-like quality of invulnerability until such time as he finishes a scripted event – at which time he is no longer important to the level designer’s wishes and is cast back into the pot of cannon fodder so that I can mow him down properly.
Getting back to the initial topic, my thought is that part of the issue between artists/level designers and programmers may very well be that the level designers don’t have a trust in the capabilities of autonomous AI agents… or even and understanding of what could be done with them.
For example, with the use of goal-based agents such as those found in F.E.A.R. (related post), rather than a designer saying “I want the bot to do A then B, then C on his way to doing the final action of D.” he could simply tell the goal-based agent that “D is a damn good goal to accomplish.” If constructed properly, the agent would then realize that a perfectly viable way of accomplishing D would be via A-B-C-D. The difference between these two methods is important. If C is no longer a viable (or intelligent looking) option, then the scripted bot either gets stuck or looks very dumb in still trying to accomplish D through that pre-defined path. The very nature of planning agents, however, would allow the agent to try to find other ways of satisfying D. If one exists, he will find it. If not, perhaps another goal will suffice.
The problem is, while AI programmers understand this concept (especially if you are the one who wrote the planner for that game), level designers and particularly artists, may not have an intuitive grasp on this. They are cut more from the cloth of writers – “and then this happened, and then this, and then it was really cool when I wrote this next thing because I wanted the agent to look smart, and then this…” That is being a writer - and is why many games continue to be largely linear in nature. You are being pulled through an experience on a string of scripted events. (See related post on Doom 3′s scripting vs. AI)
So, can the problem of designers trumping AI programmers be solved? It will always be there to some extent. But education and communication will certainly help the matter.
Yet another entry into my weekly Developer Discussion column at AIGameDev.com.
