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Markovian Interference in Experiments

NeurIPS 2022 · Reinforcement learning › Policy gradient and actor-critic · approach: Confounding-robust policy evaluation · 18 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace Naive estimator with DQ (difference in Q-functions)Toy rental MDP estimators · Toy rental MDP (N=5000)bias at t=10^4 NHelped
use unbiased OPE estimators instead of DQToy rental MDP estimators · Toy rental MDP (N=5000)varianceHurt
replace Naive with DQRidesharing dispatch experiments · Ridesharing simulator (3 alpha values)bias in ATE estimateHelped
use two-sided randomization (TSR) designs instead of NaiveRidesharing simulator · Ridesharing simulatorestimator errorNo clear effect
use TSR designs instead of NaiveToy rental MDP · Toy rental MDP (N=5000)biasHelped

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