As game developers, we’re tempted (if not outright encouraged) to code first and think later. There’s lots of good reasons for this – games are big projects, and feeling out a game’s mechanics through play is much easier than imagining them. What can we gain from planning, modelling and thinking out systems ahead of time, though? Maybe there are different ways of thinking about games that have their own power and usefulness. This week on The Saturday Paper we look at a language for modelling systems in games, and think about why it might come in handy.
Procedural generation is getting broader and deeper in games every passing month. While more and more genres are finding ways to generate parts of their play space, familiar faces are finding innovative applications for generative techniques – from universe-scale vastness to the intricate details of a single lost culture. In the midst of this rapid growth, we desperately need new and better ways to talk and think about generative design. This week on the Saturday Papers I want to show you one particular paper with an idea that’s really resonated with me lately, but that’s simple enough to use in games of all shapes and sizes, right now. Let’s jump in!
Over the last few years I’ve talked to a lot of people about procedural generation. Researchers who are interested in pushing boundaries. Developers who just wish the damn thing would work. Newcomers who wish there were better ways to get started. There are a lot of complicated problems, barriers and frustrations surrounding procedural generation (or generative software in general) and there are no easy solutions to any of them, but hopefully projects like Tracery, Cheap Bots Done Quick, PROCJAM and The PCG Book are helping towards some of them. Today I’d like to tell you about something I hope will also help solve some of these problems – a tool to help people understand, poke, tweak, improve and explore procedural generators, called Danesh.
As promised, The Saturday Papers are back, in a new format with shorter ‘seasons’ of six articles apiece. More info on the series’ future later – for now let’s get into some new research!
A lot of great storytelling relies on the intricacies and weaknesses of human character – a villain lies to further their own ends, an eyewitness misremembers a crucial detail, a fairytale hero forgets the one thing they were told not to do. Of course, all of these weaknesses are exactly the things software is designed to avoid – computers are reliable, accurate, and always follow orders. It makes for great word processing software, but it doesn’t always make for interesting games – so why don’t we try and model these weird human idiosyncracies and see where it leads?
Hello everyone! I’ve been so busy having fun with PROCJAM this week that I hardly had time to let you know that all the talks from last Saturday are online for you to watch. We had a great day launching the jam, and people are making incredible, varied, beautiful things for their jam entries. Check them out on Twitter!
If last weekend’s talks weren’t enough games-related brain thinks for you, though, this coming weekend is the second Experimental AI In Games workshop – a followup to both AIGA and EXAG of years past at the annual AIIDE conference. This year it’s a two-day workshop, packed full of cool papers and fun stuff. I thought I’d give you a brief rundown of what’s happening when, and how you can tune in online.
At the time of writing this article I am on hole two thousand, eight hundred and forty two of Desert Golfing. Continue reading
I saw an article today about the future of AI in games and suchlike and I was tempted to start tweeting about it but that inevitably leads to boring arguments and isn’t very constructive. Instead, what I’m going to do is give you a list (in no particular order) of some researchers who I think are really interesting, who are important to the future of game AI, and who have interesting things to say, and most importantly who I don’t see interviewed or talked about enough. They’d all make great people to talk to for articles, features and interviews, and each one has a research portfolio that paints a cool future for games. Go check them out!
I’ve been really excited and interested in level design recently, and reading a lot of work by folks like Robert Yang about lighting, space, and building worlds in 3D. It’s amazing stuff and it links in really well to the research I want to do right now (mostly because it’s influencing the research I want to do right now!) I wanted to write a little update about some work I did recently along these lines – building a level generator that uses in-game cameras to evaluate levels.
Recently, Appreciation Bot – my Twitter bot that responds to museum artefacts with pseudo-intellectual responses – tweeted something a bit off-colour. Not something intentionally offensive perhaps, but certainly something that would raise eyebrows were a human to tweet it. I didn’t include the tweet directly but you can view it here. Even a bot tweeting this elicited some responses from people, and I wanted to write a bit about the bot, why this happened, and what it made me think of. Before I go any further, let me just say: my bots shouldn’t offend people, and when they do it’s my fault. But this event did throw up some interesting things for me to think about. Continue reading
(This is a series of short ‘previews’ of papers to be presented at the upcoming Experimental AI for Games workshop at AIIDE 2014. Tune in live on Twitch on October 8th to catch the presentations of these papers, or find the PDFs online at http://www.exag.org)
Procedural content generation (PCG) is a thriving area for games. Everyone from indies to AAA developers is using PCG. Spelunky, Minecraft, Diablo, Dwarf Fortress, and many others use PCG at the core of the game. But are the games we have now using PCG in all the ways they can? Where has PCG been and where can it go next? Gillian Smith, in her paper “The Future of Procedural Content Generation in Games“, covers five major lenses on PCG and what unexplored areas the future might hold. Read on for a preview. Continue reading