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Found 3 papers, 3 papers with code
Imitating Cost-Constrained Behaviors in Reinforcement Learning
Generally speaking, imitation learning is designed to learn either the reward (or preference) model or directly the behavioral policy by observing the behavior of an expert.
Preference-Aware Delivery Planning for Last-Mile Logistics
However, despite many decades of solid research on solving these VRP instances, we still see significant gaps between optimized routes and the routes that are actually preferred by the practitioners.
Multiscale Generative Models: Improving Performance of a Generative Model Using Feedback from Other Dependent Generative Models
Recent work has used generative models (GANs in particular) for providing high-fidelity simulation of real-world systems.
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