摘要翻译：
音乐作曲曾经是笔和纸的活动。这些天来，音乐经常是在计算机软件的帮助下作曲的，甚至到了计算机自动作曲的地步。大多数音乐风格的创作都受规则的支配。研究表明，通过将合成的自动化、分析和验证作为一种知识表示任务，并用合适的逻辑语言将这些规则形式化，可以很容易地构建功能强大、表达能力强的智能合成工具。本文介绍了利用答案集编程建立一个自动作曲系统ANTON，该系统可以完成旋律、和声和节奏音乐的作曲，诊断人类作曲中的错误，并可作为计算机辅助作曲工具。将和声、节奏和旋律组合在一个单一的框架中，使安东在算法作曲的成长领域中独树一帜。凭借近乎实时的作曲，安东不仅可以作为交互式作曲工具的组件使用，还可以在各种应用中进行现场表演和音乐会或自动生成背景音乐。通过使用完全声明性的语言和“现成的”推理引擎，ANTON为人类作曲家提供了一个比其他现有系统更简单、更紧凑和更多功能的工具。本文已在《逻辑程序设计理论与实践》(TPLP)上发表。
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英文标题：
《Automatic Music Composition using Answer Set Programming》
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作者：
Georg Boenn, Martin Brain, Marina De Vos and John ffitch
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最新提交年份：
2010
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Logic in Computer Science        计算机科学中的逻辑
分类描述：Covers all aspects of logic in computer science, including finite model theory, logics of programs, modal logic, and program verification. Programming language semantics should have Programming Languages as the primary subject area. Roughly includes material in ACM Subject Classes D.2.4, F.3.1, F.4.0, F.4.1, and F.4.2; some material in F.4.3 (formal languages) may also be appropriate here, although Computational Complexity is typically the more appropriate subject area.
涵盖计算机科学中逻辑的所有方面，包括有限模型理论，程序逻辑，模态逻辑和程序验证。程序设计语言语义学应该把程序设计语言作为主要的学科领域。大致包括ACM学科类D.2.4、F.3.1、F.4.0、F.4.1和F.4.2中的材料；F.4.3（形式语言）中的一些材料在这里也可能是合适的，尽管计算复杂性通常是更合适的主题领域。
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  Music composition used to be a pen and paper activity. These these days music is often composed with the aid of computer software, even to the point where the computer compose parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named ANTON, that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes ANTON unique in the growing area of algorithmic composition. With near real-time composition, ANTON reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an "off-the-shelf" reasoning engine, ANTON provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems. This paper has been accepted for publication in Theory and Practice of Logic Programming (TPLP).
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PDF链接：
https://arxiv.org/pdf/1006.4948