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Incentivized Bandit Learning with Self-Reinforcing User Preferences

ICML 2021 · Bandits and online learning › Multi-armed bandits · approach: Non-stationary and structured-reward bandits · 1 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use three phases: incentivized exploration, incentivized dominance-building, then self-sustaining preferenceAt-Least-n Explore-Then-Commit · Incentivized bandit with self-reinforcing preferencesexpected regret: O(log T)Helped
Use three phases with confidence-based elimination during explorationUCB-List · Incentivized bandit with self-reinforcing preferencesexpected regret: O(log(T))Helped
Remove incentive control (ablation)Two-armed simulation with initial bias toward the suboptimal arm · Two-armed simulation, μ = [0.3, 0.5], θ = [100, 1]average regretHurt
Use incentives only during exploration, not while building dominance (ablation)Partial-incentive baseline · Two-armed simulation, μ = [0.3, 0.5], θ = [100, 1]average regretHurt
Increase feedback exponent from α = 1.5 to α = 2 (ablation)At-Least-n Explore-Then-Commit and UCB-List · Three-armed simulation, μ = [0.2, 0.4, 0.6]average regretHelped
Increase initial biases on suboptimal arms to θ = [50, 50, 1] (ablation)At-Least-n Explore-Then-Commit and UCB-List · Three-armed simulation, μ = [0.2, 0.4, 0.6]average regretHurt
Increase per-step payment from b = 1.2 to b = 1.8 (ablation)At-Least-n Explore-Then-Commit and UCB-List · Three-armed simulation, μ = [0.2, 0.4, 0.6]average regretNo clear effect
Increase per-step payment from b = 1.2 to b = 1.8 (ablation)At-Least-n Explore-Then-Commit and UCB-List · Three-armed simulation, μ = [0.2, 0.4, 0.6]total paymentHurt
Weaken incentive impact to G(b,t) = 0.5 or 0.2 (ablation)At-Least-n Explore-Then-Commit and UCB-List · Two-armed imperfect-condition simulationsaverage regretHurt
Weaken preference feedback to α = 1.0 or 0.2 (ablation)At-Least-n Explore-Then-Commit and UCB-List · Two-armed imperfect-condition simulationsaverage regretHurt
Use UCB-List instead of At-Least-n Explore-Then-CommitAt-Least-n Explore-Then-Commit · Three-armed simulationaverage regretHelped

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