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An actor-critic algorithm with policy gradients to solve the job shop
  scheduling problem using deep double recurrent agents

An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents

18 October 2021
Marta Monaci
Valerio Agasucci
G. Grani
ArXivPDFHTML

Papers citing "An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents"

4 / 4 papers shown
Title
Deep reinforcement learning for machine scheduling: Methodology, the
  state-of-the-art, and future directions
Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions
Maziyar Khadivi
Todd Charter
Marjan Yaghoubi
Masoud Jalayer
Maryam Ahang
Ardeshir Shojaeinasab
H. Najjaran
35
11
0
04 Oct 2023
schlably: A Python Framework for Deep Reinforcement Learning Based
  Scheduling Experiments
schlably: A Python Framework for Deep Reinforcement Learning Based Scheduling Experiments
Constantin Waubert de Puiseau
Jannik Peters
Christian Dörpelkus
Hasan Tercan
Tobias Meisen
OffRL
14
7
0
10 Jan 2023
Solving Mixed Integer Programs Using Neural Networks
Solving Mixed Integer Programs Using Neural Networks
Vinod Nair
Sergey Bartunov
Felix Gimeno
Ingrid von Glehn
Pawel Lichocki
...
Pushmeet Kohli
Ira Ktena
Yujia Li
Oriol Vinyals
Yori Zwols
124
244
0
23 Dec 2020
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement
  Learning
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
Cong Zhang
Wen Song
Zhiguang Cao
Jie Zhang
Puay Siew Tan
Chi Xu
60
302
0
23 Oct 2020
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