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Poster
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
in Tuesday Posters »

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.

Keywords: Bandit Algorithms · Causality
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Author Information

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

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