Deterministic Response Threshold Models of Reproductive Division of Labor Are More Robust Than Probabilistic Models in Artificial Ants

IF 1.6 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Artificial Life Pub Date : 2022-06-28 DOI:10.1162/artl_a_00369

Chris Marriott;Peter Bae;Jobran Chebib

引用次数: 0

Abstract

We implement an agent-based simulation of the response threshold model of reproductive division of labor. Ants in our simulation must perform two tasks in their environment: forage and reproduce. The colony is capable of allocating ant resources to these roles using different division of labor strategies via genetic architectures and plasticity mechanisms. We find that the deterministic allocation strategy of the response threshold model is more robust than the probabilistic allocation strategy. The deterministic allocation strategy is also capable of evolving complex solutions to colony problems like niche construction and recovery from the loss of the breeding caste. In addition, plasticity mechanisms had both positive and negative influence on the emergence of reproductive division of labor. The combination of plasticity mechanisms has an additive and sometimes emergent impact.

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人工蚂蚁生殖分工的确定性反应阈值模型比概率模型更稳健

我们实现了一种基于智能体的生殖劳动分工响应阈值模型仿真。在我们的模拟中，蚂蚁必须在其环境中执行两项任务:觅食和繁殖。蚁群能够通过遗传结构和可塑性机制，利用不同的分工策略将蚂蚁资源分配到这些角色上。我们发现响应阈值模型的确定性分配策略比概率分配策略具有更强的鲁棒性。这种确定性分配策略也能够进化出复杂的解决方案，以解决群体问题，如生态位建设和从繁殖种姓的丧失中恢复。此外，可塑性机制对生殖分工的产生既有正向影响，也有负向影响。塑性机制的组合具有附加的，有时是突发性的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Artificial Life 工程技术-计算机：理论方法

CiteScore

4.70

自引率

7.70%

发文量

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.