论文标题
多代理异质互动问题的模型
A Model for Multi-Agent Heterogeneous Interaction Problems
论文作者
论文摘要
我们介绍了一个模型，以了解多代理交互问题，以了解异质的代理团队应如何组织其资源来应对异质攻击者团队。该模型的灵感来自人类免疫系统如何应对各种病原体。该模型的关键属性是``交叉反应性''内核，它使特定的防御者类型能够对某些攻击者类型做出强烈反应，但对几种不同类型的攻击者却很弱。我们展示了由于这种交叉反应性，后卫团队如何使用几乎没有类型的防守者代理人最佳地抵消异质攻击者团队，从而最大程度地减少其资源。我们在不同的环境中研究了该模型，以表征一组指导原则，这些指导原则是针对异构代理团队的控制问题的一组指导原则，例如对亚最佳防御者分布的危害的敏感性，并且防守者之间的竞争通过对控制的分散计算进行了近乎最佳的行为。我们还将该模型与现有方法进行比较，包括加强学习政策，外围防御和覆盖范围控制。
We introduce a model for multi-agent interaction problems to understand how a heterogeneous team of agents should organize its resources to tackle a heterogeneous team of attackers. This model is inspired by how the human immune system tackles a diverse set of pathogens. The key property of this model is a ``cross-reactivity'' kernel which enables a particular defender type to respond strongly to some attacker types but weakly to a few different types of attackers. We show how due to such cross-reactivity, the defender team can optimally counteract a heterogeneous attacker team using very few types of defender agents, and thereby minimize its resources. We study this model in different settings to characterize a set of guiding principles for control problems with heterogeneous teams of agents, e.g., sensitivity of the harm to sub-optimal defender distributions, and competition between defenders gives near-optimal behavior using decentralized computation of the control. We also compare this model with existing approaches including reinforcement-learned policies, perimeter defense, and coverage control.
