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Optimising discrete event simulation models using a reinforcement learning agent

Creighton, Douglas and Nahavandi, Saeid 2002, Optimising discrete event simulation models using a reinforcement learning agent, in WSC 2002 : Exploring new frontiers : Proceedings of the 34th Conference on Winter Simulation, IEEE Xplore, Piscataway, N.J., pp. 1945-1950, doi: 10.1109/WSC.2002.1166494.

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Title Optimising discrete event simulation models using a reinforcement learning agent
Author(s) Creighton, DouglasORCID iD for Creighton, Douglas orcid.org/0000-0002-9217-1231
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Conference name Winter Simulation. Conference (34th : 2002 : San Diego, California)
Conference location San Diego, California
Conference dates 8-11 December 2002
Title of proceedings WSC 2002 : Exploring new frontiers : Proceedings of the 34th Conference on Winter Simulation
Editor(s) Yucesan, E.
Chen, C.-H.
Snowdon, J.L.
Charnes, J.M.
Publication date 2002
Conference series Winter Simulation Conference
Start page 1945
End page 1950
Publisher IEEE Xplore
Place of publication Piscataway, N.J.
Summary A reinforcement learning agent has been developed to determine optimal operating policies in a multi-part serial line. The agent interacts with a discrete event simulation model of a stochastic production facility. This study identifies issues important to the simulation developer who wishes to optimise a complex simulation or develop a robust operating policy. Critical parameters pertinent to 'tuning' an agent quickly and enabling it to rapidly learn the system were investigated.
Notes ©2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 9780780376144
0780376145
Language eng
DOI 10.1109/WSC.2002.1166494
Field of Research 019999 Mathematical Sciences not elsewhere classified
Socio Economic Objective 970101 Expanding Knowledge in the Mathematical Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2002, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30022616

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.