Some performance considerations when using multi-armed bandit algorithms in the presence of missing data

HIGHLIGHTS

• who: Xijin Chen and colleagues from the MRC Biostatistics Unit, of Cambridge, Cambridge, United Kingdom, Institute of Psychiatry have published the research work: Some performance considerations when using multi-armed bandit algorithms in the presence of missing data, in the Journal: PLOS ONE of 24/08/2022
• what: The authors investigate the impact on of this approach to deal with missing for several bandit algorithms through an extensive simulation study assuming the rewards are missing at random. The authors focus on two-armed bandit algorithms with binary outcomes in the context of patient allocation for . . .
  

   

  

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