Improving Elevator Performance Using Reinforcement Learning

@inproceedings{Crites1995ImprovingEP,
  title={Improving Elevator Performance Using Reinforcement Learning},
  author={Robert H. Crites and Andrew G. Barto},
  booktitle={NIPS},
  year={1995}
}
This paper describes the application of reinforcement learning (RL) to the di cult real world problem of elevator dispatching. The elevator domain poses a combination of challenges not seen in most RL research to date. Elevator systems operate in continuous state spaces and in continuous time as discrete event dynamic systems. Their states are not fully observable and they are nonstationary due to changing passenger arrival rates. In addition, we use a team of RL agents, each of which is… CONTINUE READING
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