Causal Bandits: Learning Good Interventions via Causal Inference
Lattimore, Finnian Rachel; Lattimore, Tor; Reid, Mark
Description
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...[Show more]
Collections | ANU Research Publications |
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Date published: | 2016 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/186528 |
Source: | Advances in Neural Information Processing Systems 29: 30th Annual Conference on Neural Information Processing Systems 2016 |
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File | Description | Size | Format | Image |
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01_Lattimore_Causal_Bandits%3A_Learning_Good_2016.pdf | 1.5 MB | Adobe PDF | Request a copy |
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