Nicholas D. Kullman

Atari-fying the Vehicle Routing Problem with Stochastic Service Requests

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We present a new general approach to modeling research problems as Atari-like videogames to make them amenable to recent groundbreaking solution methods from the deep reinforcement learning community. The approach is flexible, applicable to a wide range of problems. We demonstrate its application on a well known vehicle routing problem. Our preliminary results on this problem, though not transformative, show signs of success and suggest that Atari-fication may be a useful modeling approach for researchers studying problems involving sequential decision making under uncertainty.

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