By Topic

Reinforcement learning based on human-computer interaction

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
$31 $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

2 Author(s)
Fang Liu ; Dept. of Autom., Shanghai Jiao Tong Univ., China ; Jian-Bo Su

A novel interactive learning structure integrated with a reinforcement learning algorithm and human-computer interaction (HCI) is proposed. This interactive learning system can benefit from measurements of the distance between the current state and goal state via an operator's professional knowledge. Thus, the learning procedure is expected to be more efficient. A guess-number task is explored to evaluate the proposed learning system. Experimental results show that the learning efficiency and convergence rate are both increased compared with the normal reinforcement learning method.

Published in:

Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on  (Volume:2 )

Date of Conference:

2002