论文标题
用于多代理系统中强大动作选择的快速算法
A Fast Algorithm for Robust Action Selection in Multi-Agent Systems
论文作者
论文摘要
在本文中，我们考虑了多代理系统中强大的动作选择问题，当系统对其代理遭受最坏情况攻击时，必须保证性能。具体而言，代理人的任务是根据个性化的目标功能从共同基集中选择动作，我们旨在保护系统免受攻击。在我们的问题制定中，攻击者试图通过了解系统解决方案后消除代理的贡献来破坏系统，从而可以完美攻击。为了保护多代理系统免受此类攻击，我们旨在最大程度地提高所有代理人在攻击下的个人目标功能的最低性能。因此，我们提出了一种具有可调参数的快速算法，以平衡复杂性和性能，与最近的方法相比，时间复杂性和性能大大提高。最后，我们提供蒙特卡洛模拟，以证明所提出的算法的性能。
In this paper, we consider a robust action selection problem in multi-agent systems where performance must be guaranteed when the system suffers a worst-case attack on its agents. Specifically, agents are tasked with selecting actions from a common ground set according to individualized objective functions, and we aim to protect the system against attacks. In our problem formulation, attackers attempt to disrupt the system by removing an agent's contribution after knowing the system solution and thus can attack perfectly. To protect the multi-agent system against such attacks, we aim to maximize the minimum performance of all agents' individual objective functions under attacks. Thus, we propose a fast algorithm with tunable parameters for balancing complexity and performance, yielding substantially improved time complexity and performance compared to recent methods. Finally, we provide Monte Carlo simulations to demonstrate the performance of the proposed algorithm.
