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Transportation Marketplace Rate Forecast Using Signature Transform
Freight transportation marketplace rates are typically challenging to forecast accurately.
PDQN - A Deep Reinforcement Learning Method for Planning with Long Delays: Optimization of Manufacturing Dispatching
This paper proposes a novel method based on Deep Reinforcement Learning for developing dynamic scheduling policies through interaction with simulated stochastic manufacturing systems.
Non-Stationary Bandits with Habituation and Recovery Dynamics
Many settings involve sequential decision-making where a set of actions can be chosen at each time step, each action provides a stochastic reward, and the distribution for the reward of each action is initially unknown.
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