论文标题
具有恶意攻击的量化和分布的亚级别优化方法
Quantized and Distributed Subgradient Optimization Method with Malicious Attack
论文作者
论文摘要
本文考虑了在多代理系统中的分布式优化问题，在该系统中，代理的一部分以对抗性方式起作用。具体而言，恶意代理人通过向邻居发送虚假信息并在通信过程中消耗大量带宽来将代理网络远离最佳解决方案。我们提出了一种基于分布式梯度的优化算法，其中非恶性代理商相互交换量化信息。我们证明了解决方案与最佳解决方案的邻域的融合，并表征了在沟通受限的环境和恶意药物的存在下获得的解决方案。还提供了用于说明结果的数值模拟。
This paper considers a distributed optimization problem in a multi-agent system where a fraction of the agents act in an adversarial manner. Specifically, the malicious agents steer the network of agents away from the optimal solution by sending false information to their neighbors and consume significant bandwidth in the communication process. We propose a distributed gradient-based optimization algorithm in which the non-malicious agents exchange quantized information with one another. We prove convergence of the solution to a neighborhood of the optimal solution, and characterize the solutions obtained under the communication-constrained environment and presence of malicious agents. Numerical simulations to illustrate the results are also presented.
