arXiv:2501.17882stat.MLcs.LG2025-01

多人博弈中对抗攻击下实现近最优收益,仅用少量通信

Heterogeneous Multi-Player Multi-Armed Bandits Robust To Adversarial Attacks

  • 所有玩家采用统一策略,通过极简通信应对敌手干扰
  • 误差率接近最优,受攻击时间越长影响越大但可控
  • 适合高对抗环境下的分布式决策系统研究者

我们研究存在敌手干扰的异构多玩家多臂赌博机问题。各玩家对同一枪支的奖励分布不同,若多个玩家选择相同枪支则全部获得零奖励。敌手可同时攻击多个枪支,导致选中者均无收益。玩家不偏离预设策略,且每步至少有一个枪支未被攻击的概率严格大于零。为应对攻击,玩家可在 $O("log T$) 时间内使用单比特通信,每玩家仅能观测自身动作与奖励。我们提出一种全体玩家共享的策略,实现近最优遗憾度 $O("log^{1+δ}T + W)$,其中 $W$ 为至少一个枪支遭攻击的总时长。

原文摘要 · Abstract (English)

We consider a multi-player multi-armed bandit setting in the presence of adversaries that attempt to negatively affect the rewards received by the players in the system. The reward distributions for any given arm are heterogeneous across the players. In the event of a collision (more than one player choosing the same arm), all the colliding users receive zero rewards. The adversaries use collisions to affect the rewards received by the players, i.e., if an adversary attacks an arm, any player choosing that arm will receive zero reward. At any time step, the adversaries may attack more than one arm. It is assumed that the players in the system do not deviate from a pre-determined policy used by all the players, and that the probability that none of the arms face adversarial attacks is strictly positive at every time step. In order to combat the adversarial attacks, the players are allowed to communicate using a single bit for $O(\log T)$ time units, where $T$ is the time horizon, and each player can only observe their own actions and rewards at all time steps. We propose a {policy that is used by all the players, which} achieves near order optimal regret of order $O(\log^{1+δ}T + W)$, where $W$ is total number of time units for which there was an adversarial attack on at least one arm.

多臂赌博机对抗攻击分布式决策

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