Computational Creativity Theory

计算创造力是研究如何构建软件，在艺术和科学项目中承担一些创造性的责任。我们正处于这样一个阶段，软件可以生成图片、旋律、笑话和诗歌，可以发明新词，发现新的有趣的数学定理，并定期帮助科学家做出重要发现。这种软件可以自主使用，也可以与有创造力的人合作使用。它也被用于认知建模项目，以阐明人类和动物创造力的各个方面。在过去的十年中，计算创造力已经成熟，这一点可以从《思维与机器》杂志和《人工智能》杂志等出版物的特刊以及第一届国际计算创造力联合会议（International Joint Conference on Computational Creativity）得到证明，该会议取代了10年来在主要人工智能会议上成功举办的研讨会。被提议的领导力研究员西蒙·科尔顿（Simon Colton）是计算创造力领域公认的专家，自1996年以来一直在该领域工作。他的独特之处在于，他成功地将创意软件应用于四个不同的领域，即数学发明、视频游戏设计、平面设计和视觉艺术。他的数学理论形成软件HR产生的定理和概念发表在数学文献中；他的视觉艺术软件“The Painting Fool”制作的图片曾被展出并受到公众关注；他在帝国理工学院领导的计算创造力小组正在进行研究，帮助视频游戏公司设计下一代适应性、个性化的游戏。许多作者，如Boden， Wiggins和Ritchie，已经引入了形式主义，帮助我们更精确地了解软件的创造力。然而，目前还没有一个公认的理论能够以足够的敏锐度、覆盖范围和形式来描述软件的行为，从而能够对实现进行准确的比较。简而言之，我们没有通用的方法来说明软件B比软件a更有创造性。这阻碍了我们的研究领域，因为没有具体和正式的方法来衡量我们构建的软件的创造性，很难提出一种方法比另一种方法更有创造性的可证伪的科学假设，因此很难取得进展，也很难展示进展。有了这个奖学金，我们建议通过发展计算创造力理论（CCT）来改变这种情况。这将包括一系列模型，每个模型都包含一些概念定义和一些涉及这些定义的计算，这些定义可用于比较和对比软件的创造力。基础模型将使创造性行为的概念及其可能产生的影响更加精确，而更尖锐的模型将涵盖创造性行为的各个方面，包括意向性、解释、想象、欣赏和影响。为了充分地模拟计算机创造力，我们将过去仅仅是生成和过去通常的人工智能价值概念概括为新的领域，在这些领域中，软件被期望发明自己的美学和实用措施，并通过描述其动机、意图、方法和创新以及将其工作置于历史和文化背景中来构建其创造。拟议的研究计划的核心是CCT的发展。这是通过一系列涉及创造性语言、音乐、视觉艺术、数学和游戏的实际项目来实现的，并涵盖了包括实时生成、辅助技术和创造性合作在内的创造力模式。通过建立和传播CCT，我们将有助于将计算创造力研究带入一个新时代，在这个时代，创造力的正式概念将支撑真正丰富我们文化生活的软件系统。

Computational Creativity is the study of how to build software which takes on some of the creative responsibility in arts and science projects. We are at a stage where software can generate pictures, melodies, jokes and poems, can invent new words and discover new and interesting mathematical theorems, and regularly helps scientists to make important discoveries. This kind software can be used autonomously, or in collaboration with creative people. It is also used in cognitive modelling projects, to shed light on aspects of human and animal creativity. In the last decade, Computational Creativity has come of age, as evidenced by special issues of publications such as the Minds and Machines journal and the AI magazine, and the first International Joint Conference on Computational Creativity, which replaced 10 years of successful workshops at major AI conferences. The proposed Leadership Fellow, Simon Colton, is a recognised expert in Computational Creativity, and has been working in the field since 1996. He is unique in having been involved in successful applications of creative software to four different domains, namely mathematical invention, video game design, graphic design and the visual arts. His mathematical theory formation software, HR, has produced theorems and concepts published in the mathematical literature; his visual art software, The Painting Fool, has produced pictures that have been exhibited and attracted much public attention; and research being done in the Computational Creativity group that he leads at Imperial College is helping video games companies to design the next generation of adaptive, personalised games.A number of authors, such as Boden, Wiggins and Ritchie, have introduced formalisms which help us to be more precise about the creativity of software. However, there is no agreed upon theory which can describe the behaviour of software with sufficient acuity, coverage and formality that enables accurate comparison of implementations. In short, we have no generic way of saying that software B is more creative than software A. This has held back our field, because with no concrete and formal measures of the creativity of the software we build, it has been hard to put forward falsifiable scientific hypotheses that one approach is more creative than another, hence it has been difficult to progress, and to show progress. With this Fellowship, we propose to change this situation, by developing Computational Creativity Theory (CCT). This will comprise a series of models, each of which contains some conceptual definitions and some calculations involving those definitions which can be used to compare and contrast the creativity of software. The foundational models will make more precise the notion of a creative act and the impact they can have, and the more acute models will cover aspects of creative behaviour including intentionality, interpretation, imagination, appreciation and affect. To model computer creativity sufficiently well, we generalise past the merely generative and past usual AI notions of value, into new areas where software is expected to invent its own aesthetic and utilitarian measures, and frame its creations by describing its motivations, intentions, methods and innovations and by putting its work into historical and cultural contexts.The proposed programme of research has the development of CCT at its heart. This is informed by a series of practical projects involving applications to creative language, music, visual arts, mathematics and games, and covering modes of creativity including realtime generation, assistive technologies and creative collaborations. By building and disseminating CCT, we will help to bring Computational Creativity research into a new era, where formal notions of creativity underpin software systems which really enrich our cultural lives.