Creative Code Generation for Interactive Media

计算创造力研究是人工智能的一个分支，我们研究软件如何提高人类创造力，以及软件如何自主创造。在这一领域工作的研究人员经常开发软件，创造出某种艺术品--从绘画到诗歌，从汤谱到奏鸣曲。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，展示意向性和想象力，以及它如何构建自己的工作以增加价值。编写软件是一项困难的创造性技能，只有经过大量培训才能完成。因此，虽然它看起来很自然地适合，但从计算创造力的角度来看，还没有关于自动程序生成的认真研究。通过这个项目，我们将通过将十多年来模拟创造性行为的方法和方法应用于自动生成和测试交互式多媒体软件人工制品的问题来解决这一缺点。我们将研究让软件编写程序的方法，以及如何使这一过程尽可能具有创造性。我们将通过建立一个新的系统来测试我们的想法，该系统可以编写互动媒体程序(IMP)，范围从视频游戏到第一人称视角的体验式艺术装置。这将基于我们成功的现有合作进化软件，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造力。特别是，新系统将直接计划、编写和编辑新的程序代码，测试和评估它编写的内容，然后将其添加到它目前试图创建的任何IMP中。该代码可能描述新的对象、新的控制或得分机制，或者如何产生新的音乐或视觉效果。我们还将了解像我们的IMP设计器这样有创意的代码生成器如何创建尚未完全完成的软件。这些未完成的小鬼将能够在人们与他们交互时重写自己的代码，并在使用时改变自己。它们不仅会根据用户的反应进行自我修改，还会对世界上的外部因素做出反应，例如国际新闻或社交网络趋势。我们希望表明，由于它们不断变化的性质，这些程序被认为更令人惊讶、更具创造性和新颖性。重要的是，我们将努力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，我们开发的软件不仅仅是产生东西--它可以就如何产生东西做出决定，并传达为什么做出这些决定。我们将看看我们的IMP设计者如何决定它制作的东西是新的和有趣的，并给它提供与程序员和用户沟通的方法，告诉他们它创建了什么。我们将通过众包方法来测试我们的方法，通过这种方法，将分析来自数千名与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，并产生部分受众模型，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整个人工智能产生很大影响，因为它将带来该领域的新问题，最突出的问题是软件编写软件、自动生成自我修改的未完成的人工产物，以及从娱乐到交互媒体中的思维挑衅。此外，我们相信，这个项目将在更广泛的公众对计算机和创意产业的认知领域产生重大影响，因为它将以非常有形的方式--自动生成游戏和艺术品--突显计算机成为我们未来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.