Creative Code Generation for Interactive Media

计算创造力研究是人工智能的一个分支，我们研究软件可以增强人类创造力的方法，以及软件可以自主创造的方法。在这一领域工作的研究人员经常开发软件来创建某种人工制品--从绘画到诗歌，从汤配方到奏鸣曲。最近，我们的注意力转向了更高层次的问题，例如软件如何评估其工作，表现出意向性和想象力，以及如何构建自己的工作以增加价值。编写软件是一项困难而富有创造性的技能，只有经过大量培训的人才能完成。因此，虽然这似乎是一个自然的适合，一直没有认真的研究自动程序生成从计算创造力的角度来看。在这个项目中，我们将解决这个缺点，通过应用十多年的工作模拟创造性行为的方法和方法来自动生成和测试交互式多媒体软件人工制品的问题。我们将研究如何让软件编写程序，以及如何使这一过程尽可能具有创造性。我们将通过构建一个可以编写交互式媒体程序（IMP）的新系统来测试我们的想法，从视频游戏到第一人称视角的体验艺术装置。这将基于我们现有的成功的合作共同进化软件，该软件以完全自主的方式生成了广受欢迎的游戏，但将极大地扩展其创意能力。特别是，新系统将直接计划、编写和编辑新的程序代码，在将其添加到当前试图创建的IMP之前测试和评估它所写的内容。这个代码可能描述一个新的对象，一个新的控制或评分机制，或者如何产生一个新的音乐或视觉效果。我们还将看看像我们的IMP设计器这样的创造性代码生成器如何创建尚未完成的软件。这些未完成的IMP将能够在人们与它们交互时重写它们自己的代码，在使用它们时改变它们自己。它们不仅会根据用户的反应进行自我修改，还会根据世界上的外部因素（如国际新闻或社交网络趋势）进行自我修改。我们希望展示这些程序因其不断变化的性质而被认为更令人惊讶、更有创造性和更新颖。重要的是，我们将尝试使自动代码生成成为一个创造性的过程。在计算创造力研究中，我们构建的软件不仅仅是生成东西-它可以决定如何生成东西，并传达为什么做出这些决定。我们将看看我们的IMP设计器如何决定它所做的东西是否是新的和有趣的，并给它与程序员和用户沟通的方式，告诉他们它所创造的东西。我们将通过众包方法来测试我们的方法，其中将分析数千名与IMP互动的人的反馈，并进行机器学习练习，以确定某些假设的真实性，并生成部分受众模型用于提高输出质量。我们相信该项目将对计算创造力研究和人工智能产生重大影响一般来说，因为它将带来该领域的新问题，最明显的问题是围绕软件编写软件，自动生产“未完成”的人工制品，自我修改和互动媒体中从娱乐到思想激发的范围。此外，我们相信，这个项目将在更广泛的领域产生巨大影响，公众对计算和创意产业的看法，因为它将以一种非常切实的方式突出显示-游戏和艺术品的自动生成-计算机在未来成为我们的创意合作伙伴的巨大潜力。

Computational Creativity research is a branch of Artificial Intelligence where we investigate ways in which software can enhance human creativity, as well as ways in which software can be autonomously creative. Researchers working in this field often build software that creates artefacts of some sort - from paintings to poems, soup recipes to sonatas. In more recent times, our attention has turned to higher level issues, such as how software can evaluate its work, show intentionality and imagination, and how it can frame its own work to add value. Writing software is a difficult and creative skill which can only be performed by people after much training. As such, while it would seem a natural fit, there has been no serious study of automatic program generation from a Computational Creativity perspective. With this project, we will address this shortcoming, by applying the approaches and methodologies of more than a decade of work on simulating creative behaviour to the problem of automatically generating and testing interactive, multi-media software artefacts. We will examine ways in which we can get software to write programs, and how we can make this process as creative possible. We will test our ideas by building a new system that can write interactive media programs (IMPs), ranging from videogames to first-person-perspective experiential art installations. This will be based on our successful existing co-operative co-evolution software which has generated well-received games in a fully autonomous way, but will hugely extend its creative abilities. In particular, the new system will plan, write and edit new program code directly, testing and evaluating what it writes before adding it to whatever IMP it is currently trying to create. This code might describe a new object, a new control or scoring mechanism, or how to produce a new musical or visual effect. We will also look at how creative code generators like our IMP designer can create software that isn't quite finished. These unfinished IMPs will be able to rewrite their own code as people interact with them, to change themselves as they are used. They will self-modify not only in reaction to user responses, but also in reaction to external factors in the world, such as international news or social network trends. We hope to show that these programs are perceived as more surprising, inventive and novel, due to their ever-changing nature.Importantly, we'll be trying to make automated code generation a creative process. In Computational Creativity research, the software we build does not just generate things - it can make decisions about how to generate something, and communicate why it made those decisions. We will look at how our IMP designer can decide whether something it has made is new and interesting or not, and give it ways to communicate with programmers and users, to tell them about what it has created. We will test our approaches via a crowd sourcing methodology, whereby the feedback from thousands of people interacting with the IMPs will be analysed and subjected to machine learning exercises in order to determine the truth of certain hypotheses, and to produce partial audience models to be used to improve the quality of the output.We believe that this project will have much impact on Computational Creativity research and Artificial Intelligence in general, as it will bring to the fore new issues in the field, most notably questions around software writing software, the automatic production of "unfinished" artefacts which self-modify and the spectrum from entertainment to thought provocation in interactive media. Moreover, we believe that this project will have much impact in the broader arenas of the public perception of computing and the creative industries, as it will highlight in a very tangible way - the automatic generation of games and artworks - the massive potential for computers to become our creative partners in the future.