h1

h2

h3

h4

h5
h6
http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png

Optimisation of a Workpiece Clamping Position with Reinforcement Learning for Complex Milling Applications

; ; ; ;

In
Machine kearning, optimization, and data science: 7th International Conference, LOD 2021, Grasmere, UK, October 4–8, 2021, Revised Selected Papers / Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Giorgio Jansen, Panos M. Pardalos, Giovanni Giuffrida, Renato Umeton (eds.). - Part II, Seiten/Artikel-Nr: 261-276

Konferenz/Event:7. International Conference on Machine Learning, Optimization, and Data Science , Grasmere , UK , LOD 2021 , 2021-10-04 - 2021-10-08

ImpressumCham, Switzerland : Springer

Umfang261-276

ISBN978-3-030-95469-7, 978-3-030-95470-3, 978-3-030-95471-0

ReiheLecture notes in computer science ; 13164

Online
DOI: 10.1007/978-3-030-95470-3_20


Einrichtungen

  1. Lehrstuhl für Fertigungsmesstechnik und Qualitätsmanagement (417510)
  2. Werkzeugmaschinenlabor WZL der RWTH Aachen (417200)
  3. Lehrstuhl für Informationsmanagement im Maschinenbau (416910)



Dokumenttyp
Contribution to a book/Contribution to a conference proceedings

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85125484340
WOS Core Collection: WOS:000772650800020

Interne Identnummern
RWTH-2022-01861
Datensatz-ID: 841612

Beteiligte Länder
Germany

 GO

NationallizenzNationallizenz ; SCOPUS
QR Code for this record

The record appears in these collections:
Document types > Events > Contributions to a conference proceedings
Document types > Books > Contributions to a book
Faculty of Mechanical Engineering (Fac.4)
Documents in print
Public records
416910
417200
417510
 Record created 2022-02-17, last modified 2025-10-15
Similar records



Rate this document:

Rate this document:
1
2
3
4
5
 
(Not yet reviewed)