Integration of machine learning and optimization for robot learning

Amir Mosavi, A. Várkonyi-Kóczy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Learning ability in Robotics is acknowledged as one of the major challenges facing artificial intelligence. Although in the numerous areas within Robotics machine learning (ML) has long identified as a core technology, recently Robot learning, in particular, has been witnessing major challenges due to the theoretical advancement at the boundary between optimization and ML. In fact the integration of ML and optimization reported to be able to dramatically increase the decision-making quality and learning ability in decision systems. Here the novel integration of ML and optimization which can be applied to the complex and dynamic contexts of Robot learning is described. Furthermore with the aid of an educational Robotics kit the proposed methodology is evaluated.

Original languageEnglish
Title of host publicationRecent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016
PublisherSpringer Verlag
Pages349-355
Number of pages7
Volume519
ISBN (Print)9783319464893
DOIs
Publication statusPublished - 2017
Event15th International Conference on Global Research and Education, INTER-ACADEMIA 2016 - Warsaw, Poland
Duration: Sep 26 2016Sep 28 2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume519
ISSN (Print)21945357

Other

Other15th International Conference on Global Research and Education, INTER-ACADEMIA 2016
CountryPoland
CityWarsaw
Period9/26/169/28/16

Fingerprint

Robot learning
Learning systems
Robotics
Artificial intelligence
Decision making

Keywords

  • Machine learning
  • Optimization
  • Robotics

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Mosavi, A., & Várkonyi-Kóczy, A. (2017). Integration of machine learning and optimization for robot learning. In Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016 (Vol. 519, pp. 349-355). (Advances in Intelligent Systems and Computing; Vol. 519). Springer Verlag. https://doi.org/10.1007/978-3-319-46490-9_47

Integration of machine learning and optimization for robot learning. / Mosavi, Amir; Várkonyi-Kóczy, A.

Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016. Vol. 519 Springer Verlag, 2017. p. 349-355 (Advances in Intelligent Systems and Computing; Vol. 519).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mosavi, A & Várkonyi-Kóczy, A 2017, Integration of machine learning and optimization for robot learning. in Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016. vol. 519, Advances in Intelligent Systems and Computing, vol. 519, Springer Verlag, pp. 349-355, 15th International Conference on Global Research and Education, INTER-ACADEMIA 2016, Warsaw, Poland, 9/26/16. https://doi.org/10.1007/978-3-319-46490-9_47
Mosavi A, Várkonyi-Kóczy A. Integration of machine learning and optimization for robot learning. In Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016. Vol. 519. Springer Verlag. 2017. p. 349-355. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-46490-9_47
Mosavi, Amir ; Várkonyi-Kóczy, A. / Integration of machine learning and optimization for robot learning. Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016. Vol. 519 Springer Verlag, 2017. pp. 349-355 (Advances in Intelligent Systems and Computing).
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