Robot Soccer Using Deep Q Network

  • Jinwon Kim
  • , Bongsu Kim
  • , Jinwoo Yoon
  • , Marley Lee
  • , Sunah Jung
  • , Jae Young Choi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Reinforcement Learning is one of brilliant way to develop intelligent agents in the field of Artificial Intelligence. This paper proposes a RL algorithm called Deep Q Network and presents applications of this algorithm to the decision-making problems challenged in the RoboCup. Four scenarios were defined to develop decision-making for a SSL in various situations using the proposed algorithm. Furthermore, a Convolutional Neural Network model was used as a function approximator in each application. The experimental results showed that the proposed Reinforcement Learning algorithm had effectively trained the Reinforcement Learning agent to acquire good decision making. The Reinforcement Learning agent showed good performance under specified experimental conditions.

Original languageEnglish
Title of host publication2018 International Conference on Platform Technology and Service, PlatCon 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538647103
DOIs
StatePublished - 25 Sep 2018
Event2018 International Conference on Platform Technology and Service, PlatCon 2018 - Jeju, Korea, Republic of
Duration: 29 Jan 201831 Jan 2018

Publication series

Name2018 International Conference on Platform Technology and Service, PlatCon 2018

Conference

Conference2018 International Conference on Platform Technology and Service, PlatCon 2018
Country/TerritoryKorea, Republic of
CityJeju
Period29/01/1831/01/18

Keywords

  • Deep neural network
  • differential wheels
  • Reinforcement learning

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