Home // COGNITIVE 2019, The Eleventh International Conference on Advanced Cognitive Technologies and Applications // View article

Smart Shopping Cart Learning Agents Modeling and Evaluation

Authors:
Dilyana Budakova
Lyudmil Dakovski
Veselka Petrova-Dimitrova

Keywords: Smart shopping cart virtual learning agent; machine learning; reinforcement learning; decision tree; Ambient intelligence; holographic technology; beacon-based technology; assistive technologies.

Abstract:
The paper describes the design, implementation and user evaluation of utility and goal-based intelligent learning agents for smart shopping cart. In keeping user’s shopping list, they guide visitors through the shops and the goods in the shopping center or according to new promotions in the shops, respectively. It is envisaged that concrete implementation of the shopping agents will be running on each shopping cart in the shopping centers. The k-d decision tree and reinforcement-learning algorithm are used for agents learning. The task environment is partially observable, cooperative, deterministic, and a multi - agent environment, with some stochastic and uncertainty elements. It incorporates text-to-speech and speech recognizing technology, Bluetooth low energy technology, holographic technology, picture exchange communication system. Machine learning techniques are used for agents modeling. This kind of intelligent system enables people with different communication capabilities to navigate in large buildings and in particular to shop in the large shopping centers and maximize user comfort. Some initial user opinions of the shopping cart agents are presented.

Pages: 12 to 19

Copyright: Copyright (c) IARIA, 2019

Publication date: May 5, 2019

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-705-4

Location: Venice, Italy

Dates: from May 5, 2019 to May 9, 2019