suoju asks “I am a Ph.D. candidate doing research on AI in games. I know it is quite a broad topic, but if you can point me in a direction which I can focus on, I would really appreciate it.”
There are quite a few research topics that involve applying artificial intelligence to games, so you have lots of options…
Non-Player Character AI
Creating intelligent non-player characters (NPC) is no doubt the most researched application of AI in games. There’s still a lot of work left to do in this field, and there’s certainly a big demand too.
Decision Making and Control
Hierarchical planning seems to be the most popular research topic, and I also believe it’s the best way to go. However, it’ll take a lot of experience to make a “valuable contribution” in this field, so make sure you build on previous research as much as possible.
Here are some interesting challenges for this type of AI:
Dealing with dynamic worlds that may change while planning.
Resolving conflicting goals and enabling concurrent behaviors.
Planning with incomplete and imperfect information.
Creating planning languages that are easy to author.
Integration of planning and execution for incremental planning or lazy re-planning.
See this paper on Building Robust Planning and Execution Systems for Virtual Worlds for references and more ideas.
Making an AI that can acquire any knowledge and learn any behavior is the ultimate goal here, but you should be thinking of ways to solve useful sub-problems — if you want to finish in 3 years! Some ideas for specific AI components:
Learning behaviors based on feedback from human players.
Deriving facts from the rules of the game at runtime.
Also you may be interested to take a data-mining approach where behavior capture is used to create the logic, like the Artificial Contender middleware.
You can also research applying ML to any other aspect of game development…
AI Elsewhere in Games
Other uses of AI in games are even more popular than NPC behaviors these days. Your best bet in this area is to adapt AI techniques from other domains and apply them into games.
This area of research seems to be particularly popular, despite having very little commercial success to date. The idea is to dynamically generate story-lines that are interesting to the player. Look into StoryTron for inspiration, and GrandTextAuto for more references.
Applying AI to multiple non-player characters is an interesting challenge, but it relies on having a good AI engine for the individual actors in the first place. This is particularly useful for serious games, such as training simulations that involve multiple people coordinating together (e.g. fire drills or police investigations).
Read the AIIDE ‘07 Papers for the latest research (there are many other ideas on that page too).
This aspect of AI is under-researched, but I believe it holds lots of promise for improving the player’s experience. The idea is to build the whole player logic with a robust AI system, in order for the avatar to behave more intelligently and remove the frustrations of traditional reactive behaviors (running into walls, not doing the right thing, etc.)
Next-gen titles are taking huge amounts of time and money to create. So why not use the similar AI techniques that help create more behaviors with less time, and apply them to creating levels. For example, generating cities, buildings, rooms, or any kind of terrain that’s interesting for the player.
See this post about the Future of Game AI for more inspiration for research.
Feel free to post any further suggestions for research in the comments!