Latent order bandits require only a known partial order on actions within each latent state rather than full reward distributions, enabling UCB and posterior-sampling algorithms with regret bounds that match or exceed standard latent bandits when reward scales vary.
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Latent Order Bandits
Latent order bandits require only a known partial order on actions within each latent state rather than full reward distributions, enabling UCB and posterior-sampling algorithms with regret bounds that match or exceed standard latent bandits when reward scales vary.