Low Power Wireless Communication via Reinforcement Learning

Part of Advances in Neural Information Processing Systems 12 (NIPS 1999)

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Timothy Brown


This paper examines the application of reinforcement learning to a wire(cid:173) less communication problem. The problem requires that channel util(cid:173) ity be maximized while simultaneously minimizing battery usage. We present a solution to this multi-criteria problem that is able to signifi(cid:173) cantly reduce power consumption. The solution uses a variable discount factor to capture the effects of battery usage.