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 language | English |
|---|---|
| Title of host publication | 2016 International Conference on Intelligent Systems Engineering, ICISE 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 94-99 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781467387521 |
| DOIs | |
| State | Published - 19 May 2016 |
| Externally published | Yes |
| Event | International Conference on Intelligent Systems Engineering, ICISE 2016 - Islamabad, Pakistan Duration: 15 Jan 2016 → 17 Jan 2016 |
Publication series
| Name | 2016 International Conference on Intelligent Systems Engineering, ICISE 2016 |
|---|
Conference
| Conference | International Conference on Intelligent Systems Engineering, ICISE 2016 |
|---|---|
| Country/Territory | Pakistan |
| City | Islamabad |
| Period | 15/01/16 → 17/01/16 |
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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