Low Power Wireless Communication via Reinforcement Learning
نویسنده
چکیده
This paper examines the application of reinforcement learning to a wireless communication problem. The problem requires that channel utility be maximized while simultaneously minimizing battery usage. We present a solution to this multi-criteria problem that is able to significantly reduce power consumption. The solution uses a variable discount factor to capture the effects of battery usage.
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