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Causal Bandits: Learning Good Interventions via Causal Inference
Finnian Lattimore · Tor Lattimore · Mark Reid

Tue Dec 06 09:00 AM -- 12:30 PM (PST) @ Area 5+6+7+8 #25

We study the problem of using causal models to improve the rate at which good interventions can be learned online in a stochastic environment. Our formalism combines multi-arm bandits and causal inference to model a novel type of bandit feedback that is not exploited by existing approaches. We propose a new algorithm that exploits the causal feedback and prove a bound on its simple regret that is strictly better (in all quantities) than algorithms that do not use the additional causal information.

Author Information

Finnian Lattimore (Australian National University)
Tor Lattimore (DeepMind)
Mark Reid (Apple)

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