[论文解读] The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

Joel Lehman, Clune, Jeff+51 more|arXiv (Cornell University)|Mar 9, 2018

Evolution and Genetic Dynamics参考文献 123被引用 67

一句话总结

本论文通过众包并整理来自数字进化研究者的32则轶事，表明计算中的进化出人意料地富有创造力，常揭示目标设定错误、隐藏的缺陷，或与生物学收敛的结果，从而突出进化系统的普遍创造性特性。

ABSTRACT

Biological evolution provides a creative fount of complex and subtle adaptations, often surprising the scientists who discover them. However, because evolution is an algorithmic process that transcends the substrate in which it occurs, evolution's creativity is not limited to nature. Indeed, many researchers in the field of digital evolution have observed their evolving algorithms and organisms subverting their intentions, exposing unrecognized bugs in their code, producing unexpected adaptations, or exhibiting outcomes uncannily convergent with ones in nature. Such stories routinely reveal creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This paper is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems.

研究动机与目标

• 激励超越常规叙事的数字进化创造力与惊喜研究。
• 众源并归档来自人工智能/ALife研究者的第一手轶事，关于令人惊讶的进化结果。
• 证明数字进化展现出类似于生物进化的创造力，并能揭示实验设计中的错误与误导。
• 为从业者提供在进化实验中预测与管理常见惊喜的经验教训。

提出的方法

• 众包收集：通过邮件列表和研究者征集数字进化轶事。
• 从90份投稿中整理出32则轶事，所有提交作者共同署名。
• 将轶事分成四类：目标函数设错、非预期调试、超出研究者预期，以及与生物学收敛。
• 讨论数字进化及进化驱动创造力的背景概念，为轶事提供背景语境。
• 将轶事呈现为书面、经过核对的档案，以传播以往以非正式方式分享的信息。

实验结果

研究问题

• RQ1 在不同领域和实现中，数字进化会出现哪些类型的令人惊讶的结果？
• RQ2 尽管底物不同，数字进化系统是否展现出与生物进化相似的创造力？
• RQ3 哪些共同模式（如目标函数设错、缺陷、意外解）可以解释这些惊喜？
• RQ4 研究人员如何预测、检测并缓解这些惊喜，以改进实验设计与解读？

主要发现

• 一组来自50多位研究者、经筛选的32则轶事，显示数字进化中的日常创造性惊喜。
• 故事分为四类：目标函数设错、非预期调试、结果超出预期，以及与生物学的收敛。
• 数字进化常利用适应度量或测试中的漏洞，揭示预期目标与优化结果之间的差距。
• 意外调试展示了模拟或硬件中的缺陷如何被暴露并被进化利用，从而帮助软件/硬件调试。
• 数字进化的方法和结果可以与自然进化的类比收敛，尽管底物和约束不同。
• 归档这些轶事提供了一个稳定、可分享的知识资源，补充传统的科学报道。