Wednesday, October 22, 2014

New York, New York

In January, I will move to New York City and take up a position as Associate Professor at New York University (to be more specific in the Department of Computer Science and Engineering at the Polytechnic School of Engineering).

I am extremely excited about this. I'll be joining a growing games programme at NYU, and will be affiliated with the Media and Games Network (MAGNET) and the NYU Game Center. My new department wrote a short story about my arrival, which emphasises my work in procedural content generation and interdisciplinary collaborations. This is also my plan - continue my current main research directions (PCG, general video game playing, player modelling, game generation) while also starting new collaborative projects with the excellent people at NYU.

My five and a half years at ITU have been excellent and I've learned a lot from my amazing colleagues and developed as a researcher. I'd like to point out that I'm not moving in order to leave ITU. I'm moving because it is time to move on and seek new challenges and opportunities, and because of all the great people I will work with here and the great city I will be living in.

Maybe you want to come here as well? I am looking for two new PhD students, to start in September. You need to apply soon. And you should definitely mail me first to discuss research proposal ideas. (Hint: have a look at some of my recent papers to see what my current research interests are; these include general video game playing/generation and mixed-initiative PCG.) More information about the procedure can be found here.

Friday, October 10, 2014

Why academics and game industry don't collaborate on AI, and how we could improve the situation

In academia, there is a research community focused on artificial intelligence (and computational intelligence, which is mostly the same thing) in games. Within the games industry, there are job titles such as AI programmer and game components known as AI, and there is also a community of people self-identifying as game AI experts. Each community has their own conferences, publications and associations. The CIG and AIIDE conferences, the TCIAIG journal and the Games Technical Committee on the academic side, and the GDC AI Summit, Game AI Conference, AIGameDev website and AI Game Programmers' Guild on the industry side.However, there is surprisingly little collaboration between these communities. Instead, there is a large degree of mutual ignorance and distrust. There are a number of shining examples of crossover of industry knowledge into academia or vice versa (these are the subject of a different blog post) but these are unfortunately exceptions to the rule. Every now and then, someone comes along and points out the lack of collaboration, and vigorous discussion ensues. Every time this discussion starts, many people who have not thought about this situation are honestly surprised (they might not even have known that there was game AI research in academia or game AI R&D in industry). I've seen this debate playing out on repeat dozens of times by now, so I thought I'd share my thoughts about it in a compressed form for future reference.First, here is an incomplete list of reasons why academics and game developers that work on AI don't collaborate, and often don't even understand each other.
  • Commercial game AI and academic game AI only partly overlap. There are problems that are studied in both communities, but also technical problems in games that are considered too uninteresting to be AI by academics and academic problems that are too abstract or weird to be interesting to industry along with academic methods that won't work in real games.
  • Some (many?) academics are not really interested in doing work which is useful in games, just in using games as testbeds.
  • Some academics want to do work that is useful in games but do not know the demands and constraints of game design and development.
  • Some academics want to do work that is useful in games but do not have access to code and/or data to do that. Industry generally won't make code and data, or even APIs, available because of the need to protect intellectual property.
  • Some academics want to do work that is useful in games, but target the wrong type of games. In particular, there is the perception that only AAA games in well-established genres like FPS, RPG and RTS are worth targeting, while these games are often designed so as not to need much (interesting) AI. Why work on solving AI problems in a game which was designed not to need AI? Instead, the lust and need for new AI techniques is often stronger in the indie scene and emerging game genres.
  • Some developers in industry harbour a dislike or distrust of academic research in general. This could be because the game industry tends to see itself as an entertainment industry rather than a tech industry. It could also be because certain developers were very dissatisfied with their own university educations.
  • Some (hopefully very few) academics have a superiority complex and think their fancy degrees entitle them to talk down to the unwashed masses.
  • Some (hopefully very few) developers in industry have a superiority complex and think the fact that their software sells entitle them to tell others how Things Really Are.
  • There is little or no funding available for game-applicable AI research from government funding agencies, because games are not seen as important enough when you could instead do research on curing cancer or stopping terrorists.
  • There is no funding available for game-applicable AI research from companies, because game development companies don't support research, unlike companies in many other sectors. This could be because of the very short time horizon of game development companies. A car company or insurance company will have a 20-year strategic plan, a game company most likely won't.
  • The academic incentive system - publish, get cited, get grants - does not reward doing the "last mile" of converting your research prototype into something that could be plugged into a game engine.
  • The game industry's incentive system - make sure the next game sells or you're out of a job - does not reward trying things that might not work.
  • We simply don't go to the same places, because GDC is too expensive for academics and does not have any publication options, and academic conferences are deemed irrelevant by industry.
Perhaps most of these reasons point to an underlying difference in motivation. Researchers want to do crazy long-term stuff, developers want to do safe short-term stuff. I'm certainly of the crazy persuasion myself. But this shouldn't stop us from collaborating - rather, this complementarity is a fantastic opportunity. (Indeed, some of my own best research-work has been in collaboration with a more down-to-earth personality who tempers my wild flights of fancy.) We just need to find ways of collaborating, and stop blaming each other.I'm convinced the intersection of the interests of academic researchers and industrial developers is large enough to permit much more collaboration than we see right now. So how could we improve this situation? Here's some suggestions, again an incomplete list:
  • Respect each other. Don't slander each other.
  • Be curious about each other's work, both in terms of contribution and motivation.
  • Write blog posts (not just academic papers written in hard-to-penetrate academese) and post videos explaining your work. Goes for both academics and developers, maybe particularly for academics.
  • Find ways of making datasets and source code from commercial games available, perhaps with an NDA; alternatively ship games with an API to interface AI.
  • Make it easier to publish academic work based on collaboration with game developers. Special sessions of conferences and special issues in journals.
  • Reward developers for going to academic conferences.
  • Make it possible to publish academic papers at industry conferences, alternatively just make it cheaper to attend for academics.
  • Place more value on published (or otherwise publicly released) games and playable experiences in academics' CVs.
  • Fund applied research into game AI.
  • (Ok, I'll stop joking. Not very likely that this will happen. We'll make this work without funding because we love games and AI.)
It would also be worthwhile to point out that there are more than one way for an academic to make an impact on games. Some different modes of working - and I don't have to remind you this is an incomplete list and the different modes of working are certainly not mutually exclusive - are:
  • Read up on what industry game AI developers are interested in and which problem they find hard to tackle. This can be hard, as the information is typically not available in the form of academic papers. But is a good starting point, so is the AI Game Programming Wisdom book series. Stalking talkative developers on Twitter might also help.
  • Approach game developers and ask if you can work together with them.
  • Send your students on internships in game companies, with the objective of doing some project both you and the company find interesting. This has worked well for me in the past.
  • Use benchmarks that are based on industrially relevant games. Several of the competitions that run each year at CIG and AIIDE - in particular the BotPrize and the StarCraft competition, but to some extent also Pac-Man and Mario AI (especially if you're not just focusing on performance but on other aspects of gameplay or content generation) - are relevant here.
  • Make your own games. You don't have to work with the game industry in order to make an impact on games. In fact, you don't even have to work on the problems the industry define for you. If you are the kind of researcher who likes to come up with crazy new algorithms and then invent the problem they might solve, go one step further and build a whole game around it. Or many games. Release them out in the wild, let people play them even if they are not perfect (they will not be). They serve to prove a point, that this is AI which is relevant for games, even if it's not what the industry calls "Game AI". Lead, don't follow. Redefine what games are, and what AI is. Who's stopping you? I think this kind of research is the one which is most likely to end up being really important.
  • Participate in game jams. This is an excellent way to get started with getting your hands dirty and actually making games. At least, that's what I hear, I never have time to participate in game jams because I'm busy arguing with people on the Internet.
In short, there are so many cool things to do that we should all stop complaining about our various differences and just get on with doing great work. So what are you waiting for? What am I waiting for? I'll stop writing now.
Acknowledgements: this mail started as a reply to a mail by Robert Zubek, which was a reaction to an ongoing discussion in the AI Game Programmer Guild's mailing list, which in turn partly continues the Twitter debate following Squirrel Eiserloh's recent keynote at AIIDE. My views have been shaped by ongoing discussions about this topic with more people than I can remember in various mailing lists and conferences. People whose opinions on this topic have illuminated my own recently include Dave Mark, Alex Champandard, Tommy Thompson, Mike Cook and Luke Dickens.