论检测开放性的开放性。

IF 1.6 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Life Pub Date : 2024-08-01 DOI:10.1162/artl_a_00399
Susan Stepney, Simon Hickinbotham
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引用次数: 0

摘要

我们认为,试图量化 "开放式 "并没有达到目的:开放性的本质决定了开放式系统最终会超出其当前的行为模型,从而超出任何基于该模型的衡量标准。这给人工生命系统的分析带来了挑战,使我们得出结论:重点应放在理解开放性的内在机制上,而不是简单地试图量化它。为了证明这一点,我们对 Stringmol 自动机化学空间版本的八次长时间实验运行采用了几种测量方法。这些实验最初是为了验证空间结构能抵御寄生虫的假说。这些实验成功地展示了这种防御能力,同时也展示了一系列创新的、可能是开放式的、参与对抗寄生虫军备竞赛的行为。我们从系统一般测量方法入手,开发并使用了多种专门用于分析其中一些创新的测量方法。我们认为,在涉及开放性现象的地方,都需要一个分析过程,从系统一般的测量方法开始,到系统特定的测量方法。
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On the Open-Endedness of Detecting Open-Endedness.

We argue that attempting to quantify open-endedness misses the point: The nature of open-endedness is such that an open-ended system will eventually move outside its current model of behavior, and hence outside any measure based on that model. This presents a challenge for analyzing Artificial Life systems, leading us to conclude that the focus should be on understanding the mechanisms underlying open-endedness, not simply on attempting to quantify it. To demonstrate this, we apply several measures to eight long experimental runs of the spatial version of the Stringmol automata chemistry. These experiments were originally designed to examine the hypothesis that spatial structure provides a defense against parasites. The runs successfully show this defense, but also show a range of innovative, and possibly open-ended, behaviors involved in countering a parasitic arms race. Commencing with system-generic measures, we develop and use a variety of measures dedicated to analyzing some of these innovations. We argue that a process of analysis, starting with system-generic measures but going on to system-specific measures, will be needed wherever the phenomenon of open-endedness is involved.

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来源期刊
Artificial Life
Artificial Life 工程技术-计算机:理论方法
CiteScore
4.70
自引率
7.70%
发文量
38
审稿时长
>12 weeks
期刊介绍: Artificial Life, launched in the fall of 1993, has become the unifying forum for the exchange of scientific information on the study of artificial systems that exhibit the behavioral characteristics of natural living systems, through the synthesis or simulation using computational (software), robotic (hardware), and/or physicochemical (wetware) means. Each issue features cutting-edge research on artificial life that advances the state-of-the-art of our knowledge about various aspects of living systems such as: Artificial chemistry and the origins of life Self-assembly, growth, and development Self-replication and self-repair Systems and synthetic biology Perception, cognition, and behavior Embodiment and enactivism Collective behaviors of swarms Evolutionary and ecological dynamics Open-endedness and creativity Social organization and cultural evolution Societal and technological implications Philosophy and aesthetics Applications to biology, medicine, business, education, or entertainment.
期刊最新文献
Complexity, Artificial Life, and Artificial Intelligence. Neurons as Autoencoders. Evolvability in Artificial Development of Large, Complex Structures and the Principle of Terminal Addition. Investigating the Limits of Familiarity-Based Navigation. Network Bottlenecks and Task Structure Control the Evolution of Interpretable Learning Rules in a Foraging Agent.
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