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We consider a decentralized multi-armed bandit problem arisen in the application of cognitive radio networks, where M distributed secondary users independently search for spectrum opportunities in N channels without information sharing. The channel occupancy is modeled as an i.i.d. Bernoulli process with unknown mean. A collision happens when multiple users choose the same channel, and none or only...
We consider decentralized multi-armed bandit problems with multiple distributed players. At each time, each player chooses one of the N independent arms with unknown reward statistics to play. Players do not exchange information regarding their observations or actions. A collision occurs when multiple players choose the same arm. In this case, the reward obtained by a player involved in the collision...
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