Real-time detection of internet addiction using reinforcement learning system

Hong Ming Ji, Liang Yu Chen, Tzu Chien Hsiao

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

3 Scopus citations

Abstract

1Since Internet addiction (IA) was reported in 1996, research on IA assessment has attracted considerable interest. The development of a real-time detector system can help communities, educational institutes, or clinics immediately assess the risk of IA in Internet users. However, current questionnaires were designed to ask Internet users to self-report their Internet experiences for at least 6 months. Physiological measurements were used to assist questionnaires in the short-term assessment of IA, but physiological properties cannot assess IA in real-time due to a lack of algorithms. Therefore, the real-time detection of IA is still a work in progress. In this study, we adopted an extended classifier system with continuous real-coded variables (XCSR), which can solve the non-Markovian problem with continuous real-values to produce optimal policy, and determine high-risk and low-risk IA using Chen Internet addiction scale (CIAS) data or respiratory instantaneous frequency (IF) components of Internet users as input information. The result shows that the classification accuracy of XCSR can reach close to 100%. We also used XCSR to verify the items of CIAS and extract important respiratory indexes to assess IA. We expect that a real-time detector that immediately assesses the risk of IA may be designed in this way.

Original languageEnglish
Title of host publicationGECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages1280-1288
Number of pages9
ISBN (Electronic)9781450367486
DOIs
StatePublished - 13 Jul 2019
Event2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019

Publication series

NameGECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion

Conference

Conference2019 Genetic and Evolutionary Computation Conference, GECCO 2019
CountryCzech Republic
CityPrague
Period13/07/1917/07/19

Keywords

  • Extended classifier system with continuous real-coded variables
  • Instantaneous respiratory frequency
  • Internet addiction
  • Reinforcement learning system

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