BETA | AUTOMATED GAME DESIGN
Not content with just handling pathfinding, AI systems are now designing their own games. Douglas Heaven looks at a trend that could see the dev sector undergo its own industrial revolution. Could machines really take creativity from the hands of us mere humans?
Hello Game World
Mike Cook, creator of AI game designer Angelina, says the technology behind it acts as a good method of exploring new ideas through evaluating play patterns. Right: Angelina-made titles Revenge and Street Fightmare
ANGELINA is a remarkable games designer. At only a year old, she’s designed several arcade-style games, a handful of platformers, and is ready to tackle point- and-click adventures. She’s also not human. Halfway through a
chat over coffee in a university cafeteria, Mike Cook – gamer, computer scientist, and Angelina’s creator – stops himself. “I have to avoid calling it ‘she’ and ‘her’”, he admits. “Slightly unhealthy, but there you go.” Angelina is an AI system developed as an experiment in automated game design, part of a vision in which AI is not simply a source of increasingly sophisticated NPC behaviour, but also has a hand in designing games. “Almost everywhere has a bit of
procedural content generation, whether it’s narratives, music, whatever”, says Cook. “And all of that is backed up with what we would call AI.” Cook is part of Imperial College London’s
Computational Creativity research group, which, as he puts it: “investigates processes we call creative when we see humans do them and tries to simulate them in AI”.
THE PROCEDURAL GENERATION GAME In the past, members of the group have collaborated with studios such as Introversion on content generation and Rebellion on automated assessment of player experience, whilst another of its members is also an award-winning boardgame designer. “But higher-level stuff had never really been tackled before”, claims Cook. “We can already procedurally generate levels, rule-
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sets and behaviours – what would happen if we just put them next to each other?” Angelina’s novelty is in the way it brings
together existing procedural generation techniques and produces something bigger than the sum of their parts. This creates not just a layout or a game mechanic in isolation, but integrates both into a playable whole where layout and mechanic must work together.
Angelina simulates playing the games it
produces in a number of ways, based on varying levels of risk-taking
in human players. Mike Cook, Angelina
Cook is as careful with his terminology as he is with his pronouns. “The word ‘design’ might be too strong a word to use,” he acknowledges. “Some people aren’t too sure of the word ‘designer’. At the moment it’s definitely more compositional, bringing together ideas, but in the future that word ‘design’ will come in more prominently”. The analogy he gives is of an AI
development studio where artist and designer collaborate on ideas. “At the moment there isn’t much of that collaboration. That notion of working together is what’s new. That’s like the higher-
level creative design task, that’s what we want to move towards”. Angelina uses computational evolution
techniques to search design spaces for playable games. Using a fairly simple design language, Cook specifies certain parameters such as layout constraints and rule-set variations – effectively defining a genre. Angelina iterates through a vast number of semi-random permutations of these, where each permutation is a potential new game. The evolutionary aspect of the process
comes in when the system selects the better candidates of each iteration – or generation – and combines them to form the seeds of the next. But in Angelina’s case, there are two phases to the process. First, selecting the component game-parts – layout, mechanics – and secondly; picking a playable integration of these. Cook refers to this as ‘cooperative co-evolution’. “On the one hand, when Angelina
generates a level it looks at it and says ‘Does this look alright? Is there a bit of symmetry here, are there some interesting passageways?’ And that’s one level of evaluation. Then it puts these together to form an entire game and plays it.” “Angelina simulates playing the games it
produces in a number of ways, based on varying levels of risk-taking in human players that correlate with different degrees of skill. “ It asks questions like how often did the
player die? And where did the player die? Are they constantly dying in this one kill- corridor where I’ve made it really unfair? Looking at a level in isolation will always
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