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Game AI Roundup Week #45 2008: 13 Stories, 1 Video, 1 Paper

Novack on November 9, 2008

Weekends at AiGameDev.com are dedicated to rounding up smart links from the web relating to artificial intelligence and game development. This roundup, we have as much of content, as we did’nt have in weeks: many very good articles and blog posts around the web! Remember, there’s also lots of great content to be found in the forums here! (All you have to do is introduce yourself.) Also don’t forget the Twitter account for random thoughts!

This post is brought to you mostly by Marcos Novacovsky (aka “Novack”). If you have any news or tips for next week, be sure to email them in to editors at AiGameDev.com. Remember there’s a mini-blog over at news.AiGameDev.com (RSS) with game AI news from the web as it happens.

BrainWorks: Do Not Want!

As often, we open this week stories Roundup with an article from Ted Vessenes, who posted in his blog an article on how the BrainWorks bots perform dodging.

When a bot needs to dodge a missile, the bot considers the eight possible directions it can move in (forward, backward, left, right, and each diagonal), plus the “dodge” of standing still. Any movement direction that collides with an incoming missile is considered completely off limits. Yes, it’s bad to get “herded” where the enemy wants you to go, but that’s a situation the bot can deal with later. There’s no sense in eating a rocket now so that the bot might not take other damage later. Priority number one is always avoiding incoming damage.

Marcus Fenix don’t cheat this time



Good points for Gears of War 2’s AI, in a short paragraph that can be read at WorthPlaying.

Enemies react intelligently to your advances. You’ll find them taking cover as well as using flanking tactics when appropriate. The AI is by no means perfect, but it does an excellent job of being challenging rather than simply being hard. This is a key point of differentiation that really stands out on the higher difficultly levels. Playing through the entire single-player experience on hardcore took us about 17 hours. While there were plenty of deaths mixed in there, the vast majority of them felt like honest mistakes. There was never a sense of, “Hey, the game is cheating.”

AIIDE Dan’s Diary: Reloaded

Two weeks ago, on the 43th Roundup I commented about a post at the Dan Kline’s blog Game of Design, where he wrote a series of articles about his experiences at the AIIDE. Now he refactored those posts, and managed to turn them even better:

I’m editing these notes a week after the fact, just making it readable, but I’ve left the original voice in this piece and roughness intact because I feel the live-blogging depth is more interesting then a concise, thoughtful analysis would be. I’m happy to answer any questions people have, though, and I encourage you to contact the original presenters as well for more thorough details.

Sanjeev and his Green Destiny

Sanjeev Chandran posted in his blog and interesting article on Game AI, related to design and gameplay essence.

Generally, most research done by academics is of some use commercially. And naturally, one would expect the same to be the case in game AI research also. Only, its not. Commercial games concentrate more on the graphics, and the user experience part of the game, when compared to AI. If there is a bold announcement from the industry stating that the next edition of their game is to have the ‘next-generation-human-like-AI’, they have mostly been huge let-downs, and miserable failures. The strongest AI, in commercial games, these days are those that ‘cheat’. Have you never wondered in-game, at least in the harder levels, ‘When did he get so much points?’,’Does his nitrous never.

Semi-Official PlayStation Blog: AI series

Three Speech, a blog produced in partnership with PlayStation, published an awesome series of articles on Game AI, entitled “Intelligent design: where is AI going?”. The series, starting with a post on Autonomy, continues to -currently- up to five articles on Perception, Appearance and Deception, Navigation, and Unpredictability.

Autonomy



We all know what bad AI is. That moment a soldier gets stuck behind a small piece of foliage, doomed to complete the same running animation for the rest of eternity. Or when a group of aliens just leaps at you, spurning any opportunity for cover, in order to sacrifice themselves to your whirring mini-canon. And even if they do disappear behind a clump of rocks, they’ll usually end up poking their heads up every eight seconds in exactly the same place, allowing you to pick them off like sickly elephants at an illegal safari hunt.

Perception

Simulated sensory systems have been a part of enemy AI for several years. In the classic Thief series, guards were able to investigate noises and glimpsed movements, a feature later refined in the likes of Halo and Crysis. Nowadays, sensory data seems ever more complex, with enemies following blood trails (Alone in the Dark) or even sniffing you out on the wind (Metal Gear Solid 4). Is this a vital development? Where will it lead? Today we ask a selection of developers about bringing AI characters to their senses…

Appearance and Deception



Programming advanced AI is only part of the equation for game developers - players have to actually appreciate the intelligence of their enemies in order for it to have value; for it to be fun. Today, we’re looking at how animation and audio are being used to accentuate great AI.

Beneath all the higher ambitions for artificial intelligence in games, one basic, fundamental task remains: pathfinding. Simply telling a character how to get from A to B is a complex mathematical undertaking, and the perfect, foolproof solution remains elusive.



Unpredictability

This is the controversial one. Emergent behaviors are non-scripted, un-planned activities that intelligent game characters learn through their interactions with the game world. Even the programmer won’t know what they’re going to do. There have been some amazing examples – the giant beasts in Black and White, the cute critters in the mid-nineties artificial life experiment, Creatures… But can true enemy unpredictability work in games? Today’s AI coders aren’t so sure.

Stanford Conference Explores The State Of AI

Dan Kline, also wrote another summary of the AIIDE activities for Gamasutra.

Late last month, international AI developers and researchers alike flocked to the annual Artificial Intelligence and Interactive Digital Entertainment Conference at Stanford University.

Led by researchers Michael Mateas of Facade fame and Chris Darken of the Naval Postgradual School, the AIIDE conference focused specifically on bringing AI game programmers together with AI academics to share findings and discuss future collaborations.

PathEngine hits version 5.18

Develop brought us the news of the latest version release of the pathing middleware solution.

PathEngine has updated its pathfinding middleware to version 5.18. The latest edition brings with it significant optimisations in the pre-processing pipeline, adding a 2D overlap analysis phase to bypass BSP generation of non-overlapped terrain detail elements, and it now splits overlapping geometry into clumps for smaller BSP generation.

Believability and attributional intentionality



An interesting post at the Ian Horswill’s blog, Title TK, on simple behaviors and perceived intelligence.

The image above is a screenshot of what appears to be two child characters playing with one another while being watched by an adult. However, in actuality, what I’ve been implementing is attachment behavior, which is the response of children to stress by seeking out their caregiver (more on this another day). To implement that, I need to have something to stress the kids out. The right way to do it is to implement a real social engagement system with wariness and coy behaviors, play, turn-taking, etc. However, the first step in that is simply to make a second child and then hack the children’s appraisal systems to assign negative valence to strangers (i.e. to each other). All that does is make the kids watch one another and keep their distance from one another. For example, one won’t approach the ball if the other is too close to it. There’s no real sociality going on there.

Synthesizing Behavioral Animation

Nick Porcino, in his blog meshula.net, posted an article commenting the post by Ian Horswill (see above).

Despite the apparently complex behavior, under the covers there are simple motivators driving the animation. The children want to approach the ball, but not each other. If they get close to the ball they kick it, and since they have been backing away from each other, they appear to kick it between themselves. If they get too far from the parent, a behavior kicks in where they run to the parent for a moment, then run back to play.

Paper: Lightweight Procedural Animation…

Also, related with the two stories above, a paper from Ian Horswill, presented at the AIIDE.

Lightweight Procedural Animation with Believable Physical Interactions
Ian Horswill
2008
Download PDF

Video: Searching Game Trees



Lecture Series on Artificial Intelligence by Prof. P. Dasgupta, Department of Computer Science & Engineering, I.I.T,kharagpur. For More details on NPTEL visit http://nptel.iitm.ac.in



Stay tuned next week for more smart links from around the web!

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