Character Animation

The latest generation of consoles presents an opportunity for studios to opt for quantity over quality, by adding many more characters in their games than was previously possible. These crowds can have a dramatic impact on both gameplay and the overall experience. This article looks at how you can simulate large numbers of […]

This easter weekend at AiGameDev.com, we’ve rounded up many Smart Links from around the web, including reviews and their analysis, useful white papers, and news tidbits to keep you informed about anything relating to artificial intelligence in games.
This roundup is brought to you by Novack and Alex Champandard. If you have any news or tips […]

Over the past month, I’ve received quite a few questions about the stuff I’m working on — and some of you even seem genuinely interested! So I figured I’d take the opportunity to write a post about my master plan for 2008. It’s taken me until now to write this since there was […]

This Saturday at AiGameDev.com, there are quite a few insightful Smart Links from the blogosphere, in particular about upcoming games. Be sure to contact me if you have any news or tips for next week.
Remember there’s a mini-blog over at news.AiGameDev.com (RSS) with game AI news from the web as it happens.

While the spotlight for AI in games is often on first-person shooters or real-time strategy games, sports games also present some rather unique challenges and solutions. There certainly isn’t as much research or industry experience available to learn from, but enough to get a good overview of what happens behind closed doors at Electronic […]

Call of Duty 4: Modern Warfare received high praises from the community here. Admittedly, the AI in the game doesn’t necessarily shine for technical reasons, but it’s wonderfully put together within the whole story, and has arguably become one of the best examples of scripted level design. This article provides an overview of the development tools inside the SDK, explains how the AI logic is structured, and then dig deeper into the level scripts to show how it was put together.

Here are the results for the 1st Annual AiGameDev.com Awards for Game AI, where the best games of the year are nominated and voted by professionals, enthusiasts, and researchers in artificial intelligence for games.
As soon as the voting started, it was very clear that there were multiple polls going on at the same time: […]

This is the second article covering the research sessions at GDC 2007 in Lyon, specifically those relating to artificial intelligence in games. You can find part 1 here, and be sure to stay tuned for the final part 3 next week as part of the Thursday Theory on AiGameDev.com.
The theme for this post is […]

Next-gen animation is proving to be quite a challenge to integrate with AI! This article takes a detailed look at the kind of technology that’s used in CryEngine 2 for AI and animation. It also analyze exactly why it’s so difficult to get it working in game generally — not just for Crytek.

This week’s Thursday Theory post features an interview with Leslie Ikemoto. Leslie got her Ph.D. in animation research, notably applying artificial intelligence technology to make the resulting behaviors more believable with less effort. Not only has she published multiple papers about techniques for video games, but she has also helped studios integrate these ideas into […]

This week’s Thursday Theory post on AiGameDev.com looks into applying reinforcement learning to bridge the gap between animation control and high-level AI logic. Specifically, this review covers autonomous characters that learn to move in a dynamic world, as developed by Leslie Ikemoto from the University of Berkeley.

This tutorial on AiGameDev.com continues the series which builds simple AI logic for a simulation game. The previous article established a first design. This time, you’ll see how it can be implemented at the low-level.
It’s surprising how effective random decisions can be when they are structured together into a tree of sequential behaviors. […]

When creating character AI, your bottleneck is the presentation; there are never enough animations. Whether you’re making a big-budget production or a small independent game, you can always use more types of movement to bring your characters to life.

This article continues a series building the AI for a simulation game from the ground up. Last week, you found out what assets and libraries this project uses, and you helped figure out a first design to show off some simple but useful behaviors.
The best place to start implementing game AI is with movement […]

Halo is not only one of the best-selling game franchise of all time, but it has become a landmark in the first-person shooter genre. Thanks to Bungie’s openness, developers on the projects have been able to share their insights in the creation of the game and technology, which has influenced the whole industry significantly over the years.

In the 1970s, the roboticist Masahiro Mori speculated about a threshold of realism up to which humans empathize with robots. However, when the robot’s appearance and movement improve beyond that, humans are repulsed instead. This problem is known as the Uncanny Valley. But as the realism increases further, reactions slowly match human […]

What are rapidly-exploring random trees and how can they be a applied to games? This article looks at the theory behind this algorithm, and shows how it can be applied in practice — including to animation, navigation graph generation, and motion planning.

As the archetypal sim-game, The Sims revolutionized the industry by creating an interactive doll house, becoming the best selling PC game of all time in the process. This article looks into the smart-object technology (among other features) behind this prolific franchise, and how they are used to create an emergent simulation and emotionally rewarding gameplay.

This paper from Berkeley introduces techniques for generating fast high-quality blends between animations, so it’s possible to create responsive animations for the AI. This is done by an algorithm for finding transitions automatically, and a learning classifier to measure the realism of motion transitions to help select the best candidate.

The Thursday Theory post this week takes another whitepaper from from the Symposium on Interactive 3D Games and Graphics 2007 that’s helpful for game AI, and breaks it down into the basic ideas. See the previous post in this series for more about character animation.
This second entry is from the University of California and […]

This review of a paper from the University of Wisconsin-Madison shows how parametric motions can be combined with a motion graph, and how transitions can be crated automatically between these motions. The resulting technology is capable of generating continuous motion that looks realistic, yet is responsive to interactive control of the parameters and type of motion.

This is the last article of the Siggraph 2007 coverage on AiGameDev.com. Feel free to catch up with all the previous posts here (1, 2, 3, 4, 5, 6).
This paper is from the University of British Columbia and introduces techniques for physically-based biped locomotion control. There are two contributions in this paper:

It provides […]

Continuing the Siggraph 2007 roundup for character animation (see this previous post to catch up). The remaining papers take an approach leaning towards physical simulation rather than pure motion capture.
One paper from Seoul National University Movement Research Lab presents an biped behaviors simulated from human motion data. Once again, this project has two […]

This paper from CMU Graphics Lab presents techniques for constructing and searching interpolated motion graphs, notably by representing the desired motion as an interpolation of different paths through a motion graph, and applying an anytime A* algorithm to search through the graph of possible motion clips. This approach combines the benefits of the motion graphs for creating natural looking transitions, yet it allows the animation to be constrained physically also.

Siggraph 2007 has been running for a few days now. Make sure you catch up on the three previous posts describing control innovations for character animation.
This paper is from the Texas A&M University Graphics and Animation Lab, and involves optimizing motions based on constraints using a statistical dynamic model. The innovation in this […]

Siggraph 2007 is underway today. See the previous two articles discussing this year’s innovations character animation technology.
Today’s research project is from the Carnegie Mellon Graphics department, and involves creating responsive characters from motion fragments. There are two main innovative ideas behind this paper:

Gathering traces from the gameplay helps model player movement.
Using reinforcement learning […]

Siggraph 2007 starts tomorrow. This post continues from yesterday’s review of character animation technology, discussing how this year’s innovations can be applied to game AI.
There’s another paper from University of Washington Animation Research Labs which presents a near-optimal continuous controller. There are two major innovations used:

A low-dimensional reinforcement learning algorithm to learn a […]

Siggraph 2007 is around the corner, and that means new technology for game developers to play with! In terms of game AI, the most interesting part of the conference is character animation, as it promises to deliver realistic motion for lower investments.
One paper from University of Washington Animation Research Labs presents an active learning […]

No matter how amazing you make the AI for your actors, the resulting behaviors are fundamentally limited by what means they have to express themselves.
I call this behavior aliasing, inspired by the problems you get when you try to down-sample a high high-resolution representation (like rendering a line on a pixel display).
Aliasing of behaviors […]

For multiple behaviors to run at the same time, they must not compete over the same resources. In practice, you have two design strategies to ensure that your behaviors work well in parallel. Both of these involve getting the most out of the other modules in the game engine — where possible. […]

Creating smart actors in general is quite a challenge. Handling the latest generation of hardware and the increased expectations is particularly tough.
But what’s the most difficult from your perspective? Let everyone know what you think is the hardest part about making game AI. Post a comment below!