By Topic

Dynamic Pricing Decision in a Duopolistic Retailing Market

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Chen Li ; Institute of Systems Engineering, Huazhong University of Science & Technology, Wuhan 430074, P. R. China. liviachen@126.com ; Hongwei Wang ; Ying Zhang

Under the uncertain demand and variable environment, we studied the enterprises' dynamic decision problem on price strategies in duopolistic retailing market. In the game, two enterprises simultaneously choose their strategic variable in each period to maximize their expect revenue. We use Markov decision processes to build up the model and resolve it, and design two kinds of reinforcement learning methods which are named Nash Q-learning and Best-response Q-learning to simulate the model. Through the numerical study, we draw a conclusion that compared to the Nash Q-learning method the Best-response Q-learning is a better method to give a dynamic pricing decision in duopolistic retailing market

Published in:

2006 6th World Congress on Intelligent Control and Automation  (Volume:2 )

Date of Conference:

0-0 0