合作生存的相互依赖自组织机制

IF 1.6 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Life Pub Date : 2023-03-01 DOI:10.1162/artl_a_00403
Matthew Scott;Jeremy Pitt
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引用次数: 2

摘要

合作生存“游戏”是指在一系列灾难性事件中,除非所有人都幸存,否则没有人能幸存。这种情况可能会因反复发生的灾难的时间和规模的不确定性而进一步恶化,而生存所需的资源管理可能取决于资源开采、分配和投资的几个相互依存的子游戏,这些子游戏在幸存者之间具有相互冲突的优先级和偏好。在社会系统中,自组织一直是可持续性和生存的关键特征;因此,在本文中,我们使用人工社会的视角来研究合作生存游戏中社会构建的自组织的有效性。我们想象一个有四个参数的合作生存场景:规模,即n人游戏中的n;每次灾难的发生和程度的不确定性;复杂性,即需要同时“解决”的子游戏数量;而机会,则与参与者可使用的自组织机制的数量有关。我们设计并实现了一个由三个纠缠的子博弈(猎鹿博弈、公共池资源管理问题和集体风险困境)组成的多智能体系统,并指定了用于治理、交易和预测的三种自组织机制的算法。正如人们所预料的那样,一系列的实验表明,生存的临界质量是有一个门槛的,而且不确定性和复杂性的增加需要更多的自我组织的机会。自组织机制可能会以有害但又自我强化的方式相互作用,这一点可能更令人意想不到,这突显了作为集体自治过程中合作生存的一些反思的必要性。
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Interdependent Self-Organizing Mechanisms for Cooperative Survival
Cooperative survival “games” are situations in which, during a sequence of catastrophic events, no one survives unless everyone survives. Such situations can be further exacerbated by uncertainty over the timing and scale of the recurring catastrophes, while the resource management required for survival may depend on several interdependent subgames of resource extraction, distribution, and investment with conflicting priorities and preferences between survivors. In social systems, self-organization has been a critical feature of sustainability and survival; therefore, in this article we use the lens of artificial societies to investigate the effectiveness of socially constructed self-organization for cooperative survival games. We imagine a cooperative survival scenario with four parameters: scale, that is, n in an n-player game; uncertainty, with regard to the occurrence and magnitude of each catastrophe; complexity, concerning the number of subgames to be simultaneously “solved”; and opportunity, with respect to the number of self-organizing mechanisms available to the players. We design and implement a multiagent system for a situation composed of three entangled subgames—a stag hunt game, a common-pool resource management problem, and a collective risk dilemma—and specify algorithms for three self-organizing mechanisms for governance, trading, and forecasting. A series of experiments shows, as perhaps expected, a threshold for a critical mass of survivors and also that increasing dimensions of uncertainty and complexity require increasing opportunity for self-organization. Perhaps less expected are the ways in which self-organizing mechanisms may interact in pernicious but also self-reinforcing ways, highlighting the need for some reflection as a process in collective self-governance for cooperative survival.
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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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