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Reinforcement learning for planning of a simulatedproduction line

Werner, Hugo LU and Ehn, Gustaf LU (2018) In Master's Theses in Mathematical Sciences FMAM05 20172
Mathematics (Faculty of Engineering)
Abstract
Deep reinforcement learning has been shown to be able to solve tasks without prior knowledge of thedynamics of the problems. In this thesis the applicability of reinforcement learning on the problem ofproduction planing is evaluated. Experiments are performed in order to reveal strengths and weak-nesses of the theory currently available. Reinforcement learning shows great potential but currentlyonly for a small class of problems. In order to use reinforcement learning to solve arbitrary or a largerclass of problems further work needs be done. This thesis was written at Syntronic Software Innova-tions.
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author
Werner, Hugo LU and Ehn, Gustaf LU
supervisor
organization
course
FMAM05 20172
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Reinforcement learning, Machine learning, artificial neural networks, production planning
publication/series
Master's Theses in Mathematical Sciences
report number
LUTFMA-3341-2018
ISSN
1404-6342
other publication id
2018:E7
language
English
id
8936610
date added to LUP
2018-06-07 16:26:34
date last changed
2018-06-07 16:26:34
@misc{8936610,
  abstract     = {Deep reinforcement learning has been shown to be able to solve tasks without prior knowledge of thedynamics of the problems. In this thesis the applicability of reinforcement learning on the problem ofproduction planing is evaluated. Experiments are performed in order to reveal strengths and weak-nesses of the theory currently available. Reinforcement learning shows great potential but currentlyonly for a small class of problems. In order to use reinforcement learning to solve arbitrary or a largerclass of problems further work needs be done. This thesis was written at Syntronic Software Innova-tions.},
  author       = {Werner, Hugo and Ehn, Gustaf},
  issn         = {1404-6342},
  keyword      = {Reinforcement learning,Machine learning,artificial neural networks,production planning},
  language     = {eng},
  note         = {Student Paper},
  series       = {Master's Theses in Mathematical Sciences},
  title        = {Reinforcement learning for planning of a simulatedproduction line},
  year         = {2018},
}