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Research map / Probabilistic and scientific modeling / Causal discovery

Structural Causal Bandits: Where to Intervene?

NeurIPS 2018 · Probabilistic and scientific modeling › Causal discovery · approach: Counterfactual identification and bounds · 29 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
restrict arms to POMISs instead of intervening on all variables at onceThompson sampling · Task 3cumulative regret: 2784.8 -> 91.4Helped
restrict arms to POMISs instead of all-at-onceThompson sampling · Task 2 (IV)cumulative regret: 272.1 -> 16.1Helped
restrict arms to POMISs instead of brute-force over all subsetsThompson sampling · Task 3cumulative regret: 1469.0 -> 91.4Helped
restrict arms to POMISs instead of MISs (ablation)Thompson sampling · Task 3cumulative regret: 472.4 -> 91.4Helped
restrict arms to POMISs instead of MISs (ablation)Thompson sampling · Task 2 (IV)cumulative regret: 21.4 -> 16.1Helped
restrict arms to POMISs instead of all-at-once in Markovian modelkl-UCB · Task 1cumulative regret: 12 -> 3.0Helped
use POMIS arm set instead of all-at-oncekl-UCB · Task 1rounds to 95% optimal arm probability: 66 -> 20Helped
use MIS instead of brute-force arm set at early stage (ablation)bandit solver · Task 1optimal arm probabilityHurt

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