Three decentralized multi-agent bandit algorithms achieve near-centralized regret under heavy-tailed rewards across different information asymmetry regimes.
Some aspects of the sequential design of experiments,
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Robust Multi-Agent Bandits with Heavy-Tailed Rewards and Information Asymmetry
Three decentralized multi-agent bandit algorithms achieve near-centralized regret under heavy-tailed rewards across different information asymmetry regimes.