The HR3 System for Automatic Code Generation in Creative Settings
The HR3 System for Automatic Code Generation in Creative Settings
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发表时间：
2019
影响因子：
3.3
通讯作者：
S. Colton;A. Pease;Michael Cook;Chunyang Chen
中科院分区：
文献类型：
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作者：
S. Colton;A. Pease;Michael Cook;Chunyang Chen
我们描述了用于自动代码生成的HR3系统，以及它在创造性任务中的使用。我们概述了它构建背后的动机和总体思想，最显著的是通过识别人工智能方法论中的一些差异，当人工智能任务被视为需要解决的代码生成问题时，这些差异可以被忽略。我们在以下方面进一步描述了该方法的性质：Java API的编程接口；基于产生式规则的数据批处理；按需代码生成和检查，以及随机和元级代码库的使用。为了支持这种方法是通用的这一说法，我们描述了fiVE在三个领域的应用，这三个领域通常由单独的计算CRE系统覆盖，即数学发现、数据挖掘和生成艺术。最后，我们讨论了HR3系统的未来方向，以及这个项目可能如何解决计算创造力方面的一些更高层次的问题。
We describe the HR3 system for automated code generation, and its use in creative tasks. We outline the motivations and overall ideology behind its construction, most notably by identifying some distinctions in AI methodology which can be ignored when AI tasks are viewed as code generation problems to be solved. We further describe the nature of the approach in terms of: a programmatic interface to a Java API; production rule-based batch processing of data; on-demand code generation and inspection, and the usage of randomised and meta-level codebases. To support the claim that the approach is general purpose, we describe five applications in three areas normally covered by separate Computational Cre-ativity systems, namely mathematical discovery, datamining and generative art. We end by discussing future directions for the HR3 system and how this project might address some higher-level issues in Computational Creativity.