Atari-fying the Vehicle Routing Problem with Stochastic Service Requests

Autor:	Kullman, Nicholas D., Mendoza, Jorge E., Cousineau, Martin, Goodson, Justin C.
Jazyk:	angličtina
Rok vydání:	2019
Předmět:	FOS: Computer and information sciences Computer Science - Machine Learning Optimization and Control (math.OC) Statistics - Machine Learning FOS: Mathematics Machine Learning (stat.ML) Mathematics - Optimization and Control Machine Learning (cs.LG)
Popis:	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. 11 pages, 4 figures
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f03dd8a5848e84929a35ce428a8d55d http://arxiv.org/abs/1911.05922 Zobrazit plný text záznamu