Incorporating artificial intelligence in shopping assistance robot using Markov Decision Process

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

8 Scopus citations

Abstract

There are many challenges involved in the realization of a shopping assistance robot (SAR). The specific challenge addressed in this paper is that of incorporating artificial intelligence or decision making capability in such robot. Markov Decision Process (MDP) based formulation of the problem has been presented for this purpose. The major advantage of the MDP based approach over simple search based artificial intelligence techniques is that it can incorporate uncertainty. The proposed MDP model has been solved for optimal policy using value iteration algorithm. Furthermore, it has been shown how the reward function influences the structure of the resulting policy. The results show encouraging potential in the use of MDP based formulation for SAR.

Original languageEnglish
Title of host publication2016 International Conference on Intelligent Systems Engineering, ICISE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-99
Number of pages6
ISBN (Electronic)9781467387521
DOIs
StatePublished - 19 May 2016
Externally publishedYes
EventInternational Conference on Intelligent Systems Engineering, ICISE 2016 - Islamabad, Pakistan
Duration: 15 Jan 201617 Jan 2016

Publication series

Name2016 International Conference on Intelligent Systems Engineering, ICISE 2016

Conference

ConferenceInternational Conference on Intelligent Systems Engineering, ICISE 2016
Country/TerritoryPakistan
CityIslamabad
Period15/01/1617/01/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Markov decision processes
  • decision making
  • optimality
  • reward function
  • shopping robot

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Control and Systems Engineering
  • Instrumentation

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