Nonstochastic Multiarmed Bandits with Unrestricted Delays

被引:0
|
作者
Thune, Tobias Sommer [1 ,3 ]
Cesa-Bianchi, Nicolo [2 ,3 ]
Seldin, Yevgeny [1 ]
机构
[1] Univ Copenhagen, Copenhagen, Denmark
[2] DSRC, Milan, Italy
[3] Univ Milan, Milan, Italy
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
dWe investigate multiarmed bandits with delayed feedback, where the delays need neither be identical nor bounded. We first prove that "delayed" Exp3 achieves the 0 (\/(KT D) In K) regret bound conjectured by Cesa-Bianchi et al. [2019] in the case of variable, but bounded delays. Here, K is the number of actions and D is the total delay over T rounds. We then introduce a new algorithm that lifts the requirement of bounded delays by using a wrapper that skips rounds with excessively large delays. The new algorithm maintains the same regret bound, but similar to its predecessor requires prior knowledge of D and T. For this algorithm we then construct a novel doubling scheme that forgoes the prior knowledge requirement under the assumption that the delays are available at action time (rather than at loss observation time). This assumption is satisfied in a broad range of applications, including interaction with servers and service providers. The resulting oracle regret bound is of order min Sf3 +,3 In K + (KT + D3)1,3), where 1Sf31 is the number of observations with delay exceeding 3, and D3 is the total delay of observations with delay below 3. The bound relaxes to 0 (,/(KT D) In K), but we also provide examples where D3 < D and the oracle bound has a polynomially better dependence on the problem parameters.
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页数:10
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