English

On No-Sensing Adversarial Multi-player Multi-armed Bandits with Collision Communications

Information Theory 2021-04-27 v2 Machine Learning math.IT Machine Learning

Abstract

We study the notoriously difficult no-sensing adversarial multi-player multi-armed bandits (MP-MAB) problem from a new perspective. Instead of focusing on the hardness of multiple players, we introduce a new dimension of hardness, called attackability. All adversaries can be categorized based on the attackability and we introduce Adversary-Adaptive Collision-Communication (A2C2), a family of algorithms with forced-collision communication among players. Both attackability-aware and unaware settings are studied, and information-theoretic tools of the Z-channel model and error-correction coding are utilized to address the challenge of implicit communication without collision information in an adversarial environment. For the more challenging attackability-unaware problem, we propose a simple method to estimate the attackability enabled by a novel error-detection repetition code and randomized communication for synchronization. Theoretical analysis proves that asymptotic attackability-dependent sublinear regret can be achieved, with or without knowing the attackability. In particular, the asymptotic regret does not have an exponential dependence on the number of players, revealing a fundamental tradeoff between the two dimensions of hardness in this problem.

Keywords

Cite

@article{arxiv.2011.01090,
  title  = {On No-Sensing Adversarial Multi-player Multi-armed Bandits with Collision Communications},
  author = {Chengshuai Shi and Cong Shen},
  journal= {arXiv preprint arXiv:2011.01090},
  year   = {2021}
}

Comments

19 pages, 8 figures. Accepted to IEEE Journal on Selected Areas in Information Theory, Special Issue on Sequential, Active, and Reinforcement Learning

R2 v1 2026-06-23T19:51:12.759Z