ML Anthology

Low Power Wireless Communication via Reinforcement Learning

Timothy X. Brown
NeurIPS 1999 pp. 893-899
/neurips/1999/brown1999neurips-low/

Abstract

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.

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Text

Brown. "Low Power Wireless Communication via Reinforcement Learning." Neural Information Processing Systems, 1999.

Markdown

[Brown. "Low Power Wireless Communication via Reinforcement Learning." Neural Information Processing Systems, 1999.](https://mlanthology.org/neurips/1999/brown1999neurips-low/)

BibTeX

@inproceedings{brown1999neurips-low,
  title     = {{Low Power Wireless Communication via Reinforcement Learning}},
  author    = {Brown, Timothy X.},
  booktitle = {Neural Information Processing Systems},
  year      = {1999},
  pages     = {893-899},
  url       = {https://mlanthology.org/neurips/1999/brown1999neurips-low/}
}