Abstract
Decentralized multi-agent systems are well known for their ability to model complex systems, such as smart grids, autonomous vehicles, etc. Many decentralized multi-agent systems can be modeled as cluster-based non-cooperative games in which agents within a cluster have selfish interests different from those of agents in other clusters. In this paper, we consider a cluster-based non-cooperative game for multi-agent systems in the presence of Byzantine attacks. This is an area of research yet to be explored in non-cooperative games. Therefore, we propose a novel Byzantine-resilient online mirror descent-based decentralized Nash algorithm. We assume that the loss function is time-varying and non-convex. Also, the agents within each cluster form an unbalanced graph network. Our theoretical and simulation results show that the proposed algorithm is resilient against Byzantine attacks and computationally efficient.
| Original language | English |
|---|---|
| Pages (from-to) | 752-766 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Signal and Information Processing over Networks |
| Volume | 11 |
| DOIs | |
| State | Published - Jan 1 2025 |
Keywords
- Byzantine attacks
- mirror descent
- multi-agent systems
- non-cooperative games
- online learning
