Competition and Cooperation of Multiagent System for Moving Target Defense With Dynamic Task-Switching

Haiyan Zhao, Rongxin Cui, Weisheng Yan, Lepeng Chen

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, we present a coordinated protocol for a multiagent system (MAS) in competitive and cooperative manners for moving target defense with dynamic task-switching. The protocol comprises three components. First, we design a distance-based competitive distributed decision algorithm within an improved k-Winner-Take-All (k-WTA) framework. This algorithm generates dynamic binary task-driven signals for each agent, enabling near-optimal online grouping of MAS with arbitrary proportions. Second, we introduce a cooperative strategy that employs a shared decision-making mechanism and utilizes feedback linearization without global position information. This strategy generates motion planning signals to coordinate the agents’ actions, achieving overall cooperative behaviors such as tracking, capturing, and intercepting. Finally, we incorporate an adaptive sliding mode technique based on second-order nonlinear dynamics to enhance robustness against disturbances, ensuring uniformly ultimately boundedness (UUB) of the closed-loop system. In addition, simulations and experiments with wheeled mobile robots (WMRs) validate the effectiveness of our method.

Keywords

  • Competition and cooperation
  • moving target defense
  • multiagent system
  • task-switching
  • wheeled mobile robot (WMR)

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