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English(EN) Tuning Agent-Based Predator-Prey Models Toward Lotka-Volterra Dynamics

将基于代理的模型调整为洛特卡-沃尔泰拉动力学

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种方法，可以将基于代理的捕食者-猎物模型调整为更好地符合洛特卡-沃尔泰拉动力学。该方法使用基于特征的损失函数来优化环境和人口参数，奖励持续的振荡、相位滞后和种群有界性。该模型在基于 JAX 的 ABMax 框架中实现，允许在硬件加速器上进行高效、批处理的模拟，从而能够进行更复杂的自适应系统模拟。 AI

影响 这项研究为模拟复杂自适应系统提供了一种新颖的方法，有可能提高生态和其他领域中基于代理模型的准确性和稳定性。

排序理由 这是一篇详细介绍调整基于代理模型新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

将基于代理的模型调整为洛特卡-沃尔泰拉动力学

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这是一篇详细介绍调整基于代理模型新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Marcel van Gerven ·

    Tuning Agent-Based Predator-Prey Models Toward Lotka-Volterra Dynamics

    Recent growth in compute power has made it increasingly feasible to use large-scale agent-based models to simulate complex adaptive systems. A central difficulty is that such models contain many local rules and parameters, where small changes can lead to runaway behaviour, popula…

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