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Fiduciary Bandits

ICML 2020 · 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 EAIR-constrained exploration followed by exploitation of the best observed armFEE in the fiduciary bandit model with non-strategic agents · Fiduciary bandit modelsocial welfare: SW_{n}(\textnormal{FEE}) \geq \OPTEA-O\left(\frac{KH^2}{n} \right)Helped
Add randomized exploration phases and IC recommendations to FEEFEE for strategic agents · Fiduciary bandit modelsocial welfare: SW_{n}(\textnormal{IC-FEE}) \geq \OPTEA-O\left(\frac{KH^3}{n\xi \gamma} \right)Helped
Impose EAIR rather than leaving welfare unconstrainedFiduciary bandit mechanisms · Fiduciary bandit modelwelfare ratio: \frac{\textnormal{OPT}}{\OPTEA} \geq H\left(1-e^{-\frac{K}{H}}\right)Hurt
Replace EAIR with the stricter EPIR guaranteeFiduciary bandit mechanisms · Fiduciary bandit modelwelfare ratio: \frac{\OPTEA}{\OPTEP} \geq \frac{H+2}{3}\left(1-e^{-\frac{K-2}{H}} \right)Hurt
Allow EPIR exploration rather than requiring delegate-greedy recommendationsFiduciary bandit mechanisms · Fiduciary bandit modelwelfare ratio: \frac{\OPTEP}{\OPTDEL} \geq \frac{H}{3}\left( 1-e^{-\frac{K-2}{H}}\right)Helped

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