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Earlier this month, the IEEE Conference on Computational Intelligence in Games took place at the IT University in Copenhagen. Over 100 researchers from around the world showed up to present their very latest research. In between, there were inspiring keynotes from highly respected figures in the research community, with topics ranging from A-life and bottom-up aesthetics to top-down drama management. AiGameDev.com was there to cover the event, and I (Alex Champandard) gave a tutorial on the first day too.

The rest of this report includes some background about the conference (including things I learned from my first attendance to this event), the state of industrial-academic collaboration (and why many researchers were so depressed because of me), a report from the various competitions run at CIG 2010 (such as the 2K BotPrize and Mario AI), and finally further references so you can find out more about the research track and the papers presented.

While animation and navigation technology has matured significantly over the years, combining the two together remains quite a challenge! Games like HEAVY RAIN include scenes with few pedestrians that must avoid each other (e.g. on a sidewalk), as well as huge groups that form the illusion of a crowd (e.g. in the station). What techniques are used to implement such situations, and how can the results be improved?

In this all-star panel from the Paris Game AI Conference 2010, you'll hear different perspectives on the problem, from the programming team at Quantic Dream (Bertrand Faure, Jean-Charles Perrier) to leading researchers on procedural animation (Ken Perlin), and one the best independent AI developers (Mikko Mononen)! With their combined wisdom you'll hear solutions to the crowd problem compared to smaller groups of agents, and the best way to integrate it with character animation.

Over the past decade, blend trees have established themselves in the games industry as a reliable and flexible technique for animating game characters. However, it can take a lot of development time to build up an efficient runtime and powerful toolset, and obviously middleware companies are stepping up!

In this interview-style presentation with Jason Turbin, you'll find out everything you need to know about Havok Behavior, the middleware animation system that powers WORLD OF ZOO (among many other titles). Jason goes behind the scenes into the architecture and implementation of Havok Behavior, and provides insights into the tools and how they are used.

The most recent game in the survival horror series, SILENT HILL: SHATTERED MEMORIES recently became famous by psychologically profiling its players. The game received acclaim from the press and players alike, in particular for getting into people's head — and adding replayability to the game. But what combination of tricks and techniques were used to pull this off?

In this presentation from the Paris Game AI Conference 2010, you'll hear Gwaredd Mountain (technical director at Climax) explain the player modelling used by the game to infer which of the Big Five personality profile is dominant in each player. He also explains what data drives the psychological profiling and how it affects the content in the game to deliver a customized experience to the player. He'll also share some insights on its integration within the game's design.

BATTLEFIELD: BAD COMPANY 2 is most recent FPS from EA's acclaimed DICE studio. The game certainly has its fair share of AI challenges — including many BATTLEFIELD-specific problems such as finding cover in highly dynamic environments and driving physically realistic vehicles. How did a AAA studio known for its multiplayer games set out to build the AI a story-driven game in BAD COMPANY 1, and how did it evolve for the sequel?

In this keynote from the Paris Game AI Conference 2010, Lead AI Programmer Mikael Hedberg shares some insights into AI for the BAD COMPANY series, in particular the changes the team made for the most recent iteration and how it affected the overall experience. You'll also hear how the Frostbite AI evolved from its original use in multiplayer bots, and how the results differ from many other game's AI.

If you've been following recent trends in game AI, you could think of navigation meshes as an angry horde set to kill off waypoint graphs. Meshes are everywhere: from the various middleware libraries presented in Paris last month like Autodesk's Kynapse, PathEngine, or Havok's to open-source implementations like Recast as well. Some veteran developers have even declared waypoint-based approaches to be obsolete...

Yet, waypoint graphs are still regularly used in the games industry. I personally often recommend them — especially to independent developers — since they're a simple and effective approach to navigation, and if you're going to implement something yourself for a game, you might as well use waypoints and save yourself the torment of writing a robust navigation mesh that you may never make the most of!

The recent release of AlienSwarm (free on Steam) is a perfect illustration of how waypoints are still used in practice, and are supported by Valve's Source engine. In this post, you'll find some insights into the code from the SDK (also available) as well as screenshots from the game itself. Oh, and be sure to join our official AiGameDev.com Group on the Steam Community!

Two years ago, I briefly met Jason Della Rocca in Paris and he was genuinely surprised that our inaugural Game AI Workshop '08 sold out to a whole fifty (50) people! I got a metaphorical pat on the back, and went back to work. Last year, our Game AI Conference '09 found its home at the CNAM, but we didn't have any fancy badges, no branding signs or posters, and one of our coffee breaks accidentally turned into a tea break *gasp*. Yet still almost two hundred developers (200) joined us in Paris over two days, and a community was born.

This year, returning to the CNAM allowed us to combine the conference plus a workshop, and focus on the little details that make the difference, badges, posters, signs, color schedules, etc. (It doesn't sound like much, but you should have seen them :-) Certainly it was far from perfect, with registration bottlenecks and no soft drinks, but it didn't matter! Game developers worldwide joined us again and nearly three hundred (300) people attended over three days, forcing us to upgrade to the biggest amphitheatre.

The common theme for all these events was a genuine passion for AI and games, from the speakers to the program committee (Phil Carlisle, Mikko Mononen, William van der Sterren), including the organization committee (Axel Buendia, Petra Champandard-Pail, Stephane Natkin) and everyone who volunteered to help. With that kind of energy going into the conference, what came out was a fantastic community and friendly atmosphere that no trade-show or generic developer's conference could match.

The typical decision-making systems used in games these days have many inter-dependencies; even with HFSM or behavior trees it's hard to extend the AI without having to consider the whole set of decisions. Rule-based systems provide a more modular approach to certain problems, which can help build more scalable AI using formal logic.

In this masterclass with Richard Evans, Lead Simulation Engineer at Maxis and Head of AI on THE SIMS 3 who was also Lead AI Programmer on BLACK & WHITE, you'll hear about using rule-based systems in practice. Richard will discuss the application of rule-based systems, logic programming and deontic logic in games — using examples from prototypes and previous games — and how they can help you in your game.

Fixing bugs remains one of the most time consuming tasks for game developers, and no matter how careful you are with architectural choices or automated testing, problems will creep in at the worst possible time! In terms of AI, decision making processes are often quite complex, and as such, debugging AI often requires significant help from debug visualization.

This masterclass looks into the kind of rendering frameworks you need to build to support debug visualization, and the different ways this can be done in practice. You'll also hear guidelines about what to support upfront and what to expect during production.

To work in games studio you have to be keen to work on general "game development" tasks, as the time you spend on AI can be surprisingly small... However, if you're keen to focus entirely on game AI, then a job in middleware may be the solution.

In a strange coincidence, the middleware companies sponsoring AiGameDev.com (who make it possible for us to do what we do), are hiring! Read on to find opportunities on-site worldwide at PathEngine, Spir.Ops, Havok or Artificial Technology. Also, we're organizing an open forum during the second day of the Paris Game AI Conference 2010, and there will be many opportunities for networking and looking for jobs.

Role-playing games often exhibit challenging worlds for the AI to deal with, and BioWare's recently released DRAGON AGE: ORIGINS is no exception. It features large worlds with multiple co-operative NPCs, player avatars that can be automatically controlled at the click of a mouse, plus dynamic area effects and unpredictable dynamic obstacles. How are pathfinding and navigation systems built to deal with all these requirements?

In this interview with Nathan Sturtevant, contractor at BioWare and Associate Professor at the University of Alberta, you'll learn about the pathfinding of DRAGON AGE: ORIGINS in all its details. In particular Nathan will explain the process of rewriting the existing system, the functioning of the navigation system as well as the low-level details about optimization and implementation. You'll also see how a mere three bits in the low-level representation enabled entire game features!

Over the years, Paradox Entertainment has built a reputation for the historical accuracy and the detail of the simulation in its grand strategy games, such as the EUROPA UNIVERSALIS and HEARTS OF IRON series. In games of this scale and detail, how is the AI built compared to other RTS-style AI?

In this text interview with Henrik Fåhraeus, you'll find out some details about the AI in the game, in particular its internal architecture, how it maintains a strategy over time, and how special case behaviors work under the hood. You'll also see what that means for your game.