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创造游戏生成器所面临的挑战

发布时间:2016-11-30 17:53:12 Tags:,,,,

作者:Michael Cook

在过去几年里,游戏设计已经成为我每天研究重点中非常重要的一部分,当我更深入了解它并亲自进行尝试时,我便能从中获得更多乐趣。想想系统,交流理念,鼓励或令人沮丧的行为,平衡策略,以及留给人们惊喜,所有的这些都是将游戏设计变成具有奖励性和创造性的活动元素。在过去几年里我发现了一些有关创造出更具易用性的游戏设计的重要步骤,如Twine和PuzzleScript的创造都能帮助人们直接进行游戏创造并避开各种技术障碍。像Game Maker和Construct等受欢迎的技术也标志着更多没有编程背景的人也能够去创造游戏。

现在我正致力于Metamakers Institute,这个来自康沃尔法尔茅斯大学的一支研究小组。我们会基于全新且有趣的方式去使用具有创造性的AI,而现在我们正致力于研究生成软件如何在游戏设计方面帮助人们。作为我们工作的一部分,我同时也在创造一款名为“No Second Chance”的应用(简称N2C),你可以用它去玩游戏并设计游戏,这里同时也有一些特殊的AI秘方。

No Second Chance(from tuicool)

No Second Chance(from tuicool)

No Second Chance(NSC)

NSC是关于设计并玩小型实体游戏。从某种程度上来看每一款游戏都是不同的,但它们也拥有一些共同点:在屏幕中心总是会出现一个目标,你可以使用手指去移动它;你需要获得5个点才能获胜(游戏邦注:基于不同游戏规则玩家或许可以获得圆圈,并且有些圆圈还需要玩家花费点数)。除了这两个简单的内容外,游戏中还存在许多可能改变的不同元素,即包括圆圈的大小,移动的速度,它们的颜色,它们的移动走向,它们是否值得玩家花费点数去获取,当它们彼此碰触时会发生什么等等。这种灵活性意味着游戏将需要各种技能,如快速反应能力,够稳的手,耐心的移动,精明的眼力等等。举个例子来说吧,如果圆圈需要花几秒时间才能抓住目标,并且碰到你的手时会被弹开,那么你就必须小心围绕着圆圈移动避免它们跑出屏幕。如果圆圈很快就能占有但却会因为其它类型的圆圈(如小行星)的闯入而被摧毁,你便需要快速行动去保护你所获得的分数了。

如今N2C拥有两种主要的使用模式:一种模式是玩你自己或其它N2C用户所创造的游戏,另一种模式是使用我们简单的设计界面(即由按键和滑条所组成)。我认为这有点像是一个口袋大小的空间,并伴随着许多等待探索的模式。有时候你可以通过游戏去探索该空间,因为NSC游戏并不包含说明,所以每款游戏都是关于尝试,测试与精通的发现过程。有时候你会通过设计,尝试游戏理念,测试规则以及进行一些小小的改动去探索这一空间。而最重要的是,有时候你会让应用自己帮你进行探索—-我们拥有一个嵌入式AI能够为一个全新游戏设计生成,测试并建议出发点。但现在这仍然处于试验阶段,我们希望更多N2C用户能够使用生成系统去决定设计起点,因为这是受到部分完成的游戏设计的启发。

部分生成

对于人类的游戏设计来说,使用生成游戏作为起点真的是一种很有趣的人类与计算机的互动。我们并不希望系统随机生成一些糟糕或不可能的游戏,因为这并不能带给用户多少帮助。N2C的设计空间似乎会局限于我之前所描述的内容,但从整体上来看在空间里如果存在许多随机点的话真多很糟糕。所以我们希望我们的系统能够聪明地找出真正“有效的”游戏。不过同时我们也不希望系统创造出太过完美不用任何完善的游戏,因为这会导致用户不去改变任何内容或者不去创造属于自己的设计。所以我们真正希望的是能够创造出“带有缺陷的宝石”的系统,即它们可以拥有一个不错的理念,但是在某种程度上它们的设计又可以不用太过完美。也许用户需要做些调整去避免玩家受挫,或者需要改变滑条去提高挑战性。也许有人会认为游戏太简单而去提高难度,但也有用户会有相反的想法。这里的要点在于,这是能够带给你灵感和创造性起点的系统。

其实创造一款带有缺陷的游戏和创造一款完美的游戏一样困难,特别是当你想要知道为什么它出现问题或者是否能够修改它时。对于像台式机上注重模拟的实时实体游戏来说这就已经很困难了,就更别提小型手机游戏了。许多自动游戏设计研究能够测试无数游戏并从中获取一些理念和信息,但是我们所使用的设备(以及我们用户的关注范围)并不能持续较长时间让我们做到这些。所以我们正在探索一些新理念,如使用深度学习内容去分析能够创造的游戏类型的隐藏架构的设计空间,或者分析现有游戏设计去发现设计参数及其对于游戏设计的影响之间的关系。希望我们能够创造一个能够让人们觉得使用N2C创造游戏与使用它去玩游戏一样有趣的游戏生成器。

本文为游戏邦/gamerboom.com编译,拒绝任何不保留版权的转发,如需转载请联系:游戏邦

Deep Space Exploration: Generating Design Challenges

by Michael Cook

Over the past few years game design has become a bigger and bigger part of my everyday research focus, and the more I find out about it and try it out for myself, the more fun I find it. Thinking about systems, communicating ideas, encouraging or discouraging behaviour, balancing strategies, leaving surprises for people to find—all of these things make design games a really rewarding creative activity. The last five years have seen some really important steps towards making game design more accessible to people, like the creation of Twine and PuzzleScript that have helped people cut straight to game-making and bypass a lot of technical barriers. The popularity of tools like Game Maker and Construct is also a sign that more people are able to start creating games without a deep programming background, which is fantastic news.

I’m currently working at the Metamakers Institute, a research group based at Falmouth University in Cornwall. We’re interested in using generative and creative artificial intelligence in new and interesting ways, and right now we’re looking at how generative software might help people design games. As part of our work we’re making an app called No Second Chance, or N2C for short—you can use it to play games and design games, but there’s also a bit of special AI secret sauce dabbed on top. We’re actually interested in bringing on some new testers, so if your interest is piqued by this blog post do contact us to get on our TestFlight (there’ll be another link at the bottom of the page).

No Second Chance

NSC is about designing and playing small physics-based games. Each game is different in some way, but they all have a few things in common: there’s always a target in the center of the screen which you move with your finger; and you always need five points to win (circles can be captured depending on the game rules, and some circles are worth points – again, depending on the game rules). Besides these two simple facts, there’s a huge set of variable factors that can change in a game, from how big the circles are, how fast they move, what colour they are, where they move towards, whether they’re worth points to catch, what happens when they touch other circles and more (in fact, there are over 70 parameters in an N2C game at the moment, and we’re adding cool new ones all the time). This flexibility means that games might demand all kinds of skills, like quick reflexes, a steady hand, patient movement, a careful eye, or all sorts of other things. For example, if the circles take several seconds to latch on to the target, but are also gently repelled by your finger, you have to carefully shepherd them around in circles to avoid them fleeing off the screen. If the circles latch quite quickly but are destroyed by other circle types flying across the screen like asteroids then you might need to quickly zip around to protect your scored points.

N2C has two main modes of use right now: a mode for playing games made by you or other N2C users, and a mode for designing games using our simple design interface made up of buttons and sliders. But really, N2C isn’t a design app or a game. I’ve begun to think about it a bit like a pocket-sized possibility space, with different modes for exploring it. Sometimes you explore that space by playing, because NSC games don’t have instructions so each game is a discovery process of poking and testing and (hopefully) mastery. Sometimes you explore that space by designing, trying out ideas for games, testing rule combinations and making small tweaks. And most importantly, sometimes you let the app itself help you explore it—we have an AI built into the app that can generate, test and suggest starting points for a new game design. It’s still in an experimental stage right now, but we’re hoping that a lot of N2C users will ask the generative system for design starting points, as a way of becoming inspired by being given a partially-finished game design.

Partial Generation As Co-Creation

Using generated games as a starting point for human game design is a really interesting kind of human-computer interaction. We don’t want the system to randomly produce bad or impossible games, because that doesn’t really help the user much. The design space of N2C might seem constrained from the description I gave earlier, but combinatorially it’s huge and a lot of the random points in the space are really bad. So we definitely want our system to be clever enough to find ‘okay’ games. But equally, we don’t want the system to produce polished, perfect, unimprovable games, because that might discourage users from changing things or making the design their own—it turns out this is just as well, because generating perfectly designed games is pretty hard. One way of looking at this is that we want our system to generate games that are ‘flawed gems’—they have the seed of a good idea, but their design is broken or incomplete in some way. Maybe it needs a little tweak to not be frustrating, or a slider changed just a little to be challenging. Maybe one person would think it was too easy and make it harder, and another user do the exact opposite. Maybe it sparks off an idea that’s totally different and you go and make that instead. The point is that it’s an inspiration, a creative starting point for you to go and do something.

Making a flawed game is almost as hard as making a perfect game though, especially if you want to know why it’s broken or whether it’s possible to fix it. It’s even harder for real-time, physics-based games like N2C which are computationally intensive to simulate on a desktop machine, let alone a small mobile phone. A lot of automated game design research can playtest thousands of games to try out ideas and get information, but the devices that we’re working with (and the attention spans of our users) wouldn’t last nearly long enough to do that. So we’re exploring new ideas, like using deep learning to analyse the design space for hidden structure about the types of games that can be produced, or analysing existing game designs to uncover relationships between design parameters and their impact on game designs. Hopefully we’ll be able to build a game generator that excites and inspires people such that making games with N2C will be as much fun as playing them.

Join The Beta!

Right now we’re opening up an early beta version of the app to people for testing and feedback. We can’t accommodate everyone, but if you’re interested in trying the app out and giving us some feedback, and you have an iOS device with TestFlight installed, you can take part by emailing testflight -at- metamakersinstitute.com with “MeMeMe” in the subject line.(source:gamasutra

 


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