The Deceptive Bandit Problem: Exploratory Coupling and the Fragility of Multi-Agent Learning

arXiv:2610.09120 · cs.LG, cs.SY, eess.SY · Submitted 2026-10-06 · Read on arXiv

cs.LG, cs.SY, eess.SY

Submitted: 2026-10-06

Updated: 2026-10-06

Terminology

• Nash Equilibrium — 18× in this paper · explained in 2 episodes
• Reinforcement Learning — 5× in this paper · explained in 4 episodes
• Action Space — 4× in this paper · explained in 1 episode
• Convergence Guarantees — 3× in this paper · explained in 3 episodes
• Information Asymmetry — 2× in this paper · explained in 2 episodes
• Regret — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Conference on Decision and Control — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Differentially Private — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• Adversarial Policies: Attacking Deep Reinforcement Learning

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