Replicable Dueling Bandits

The paper introduces the first algorithms for replicable dueling bandits, ensuring that two runs with shared internal randomness and independent comparison outcomes select the same ordered pair in every round with high probability. Under relaxed stochastic transitivity, the authors achieve expected regret ×O(γ^8 K^4 H_p/ρ^2), while under strong stochastic transitivity they improve this to ×O(K^2 H_p/ρ^2). For linear dueling bandits, a regret bound of ×O(d^3√T/(c_μρ)) is presented, and experiments confirm both replicability and sublinear regret.

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