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"Scalable Reinforcement Learning for a Simulated Production Line"

Seminarium
Gustaf Ehn, Pi11 & Hugo Werner, Pi12 presenterar sitt examensarbete

Abstract

Deep reinforcement learning has been shown to be able to solve tasks without prior knowledge of the dynamics of the problems. In this thesis the applicability of reinforcement learning on the problem of production planning is evaluated. Experiments are performed in order to reveal strengths and weaknesses of the theory currently available. Reinforcement learning shows great potential but currently only for a small class of problems. In order to use reinforcement learning to solve arbitrary or a larger class of problems further work needs be done. This thesis was written at Syntronic Software Innovations.

 

Keywords: Reinforcement learning, Machine learning, artificial neural networks, production planning

 

Tid: 
2018-02-15 13:15 till 14:15
Plats: 
MH:210B Sigma
Kontakt: 
niels_christian.overgaard [at] math.lth.se

Om händelsen

Tid: 
2018-02-15 13:15 till 14:15
Plats: 
MH:210B Sigma
Kontakt: 
niels_christian.overgaard [at] math.lth.se

Box 117, 221 00 LUND
Telefon 046-222 00 00 (växel)
Telefax 046-222 47 20
lu [at] lu [dot] se

Fakturaadress: Box 188, 221 00 LUND
Organisationsnummer: 202100-3211
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