CNN-LSTM-Based Deep Recurrent Q-Learning for Robotic Gas Source Localization

Iliya Kulbaka, Ayan Dutta, Ladislau Boloni, O. Patrick Kreidl, Swapnoneel Roy

Research output: Chapter or Contribution to BookLiterary contribution

Original languageEnglish
Title of host publicationProceedings - 22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023
EditorsM. Arif Wani, Mihai Boicu, Moamar Sayed-Mouchaweh, Pedro Henriques Abreu, Joao Gama
Pages1060-1065
Number of pages6
ISBN (Electronic)9798350345346
DOIs
StatePublished - 2023
Event22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023 - Jacksonville, United States
Duration: Dec 15 2023Dec 17 2023

Publication series

NameProceedings - 22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023

Conference

Conference22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023
Country/TerritoryUnited States
CityJacksonville
Period12/15/2312/17/23

ASJC Scopus Subject Areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Keywords

  • CNN
  • Deep Q-Learning
  • Gas source localization
  • LSTM
  • Mobile robot

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