A Generalized Gittins Index for a Class of Multiarmed Bandits with General Resource Requirements
نویسندگان
چکیده
منابع مشابه
A Generalized Gittins Index for a Class of Multiarmed Bandits with General Resource Requirements
We generalise classical multi-armed and restless bandits to allow for the distribution of a (fixed amount of a) divisible resource among the constituent bandits at each decision point. Bandit activation consumes amounts of the available resource which may vary by bandit and state. Any collection of bandits may be activated at any decision epoch provided they do not consume more resource than is...
متن کاملComputing an index policy for multiarmed bandits with deadlines
This paper introduces the multiarmed bandit problem with deadlines, which concerns the dynamic selection of a live project to engage out of a portfolio of Markovian bandit projects expiring after given deadlines, to maximize the expected total discounted or undiscounted reward earned. Although the problem is computationally intractable, a natural heuristic policy is obtained by attaching to eac...
متن کاملMulti-Armed Bandits, Gittins Index, and its Calculation
Multi-armed bandit is a colorful term that refers to the di lemma faced by a gambler playing in a casino with multiple slot machines (which were colloquially called onearmed bandits). W h a t strategy should a gambler use to pick the machine to play next? It is the one for which the posterior mean of winning is the highest and thereby maximizes current expected reward, or the one for which the ...
متن کاملFour proofs of Gittins' multiarmed bandit theorem
We study four proofs that the Gittins index priority rule is optimal for alternative bandit processes. These include Gittins’ original exchange argument, Weber’s prevailing charge argument, Whittle’s Lagrangian dual approach, and Bertsimas and Niño-Mora’s proof based on the achievable region approach and generalized conservation laws. We extend the achievable region proof to infinite countable ...
متن کاملMultiarmed Bandits With Limited Expert Advice
We consider the problem of minimizing regret in the setting of advice-efficient multiarmed bandits with expert advice. We give an algorithm for the setting of K arms and N experts out of which we are allowed to query and use only M experts’ advice in each round, which has a regret bound of Õ (√ min{K,M}N M T ) after T rounds. We also prove that any algorithm for this problem must have expected ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematics of Operations Research
سال: 2009
ISSN: 0364-765X,1526-5471
DOI: 10.1287/moor.1080.0342