Making virtual learning environment more intelligent: application of Markov decision process
Suppose there exist a Virtual Learning Environment in which agent plays a role of the teacher. With time it moves to different states and makes decisions on which action to choose for moving from current state to the next state. Some actions taken are better than some others. The transition process...
Saved in:
Main Author: | Dalia Baziukaitė |
---|---|
Format: | Article |
Language: | English |
Published: |
Vilnius University Press
2004-12-01
|
Series: | Lietuvos Matematikos Rinkinys |
Subjects: | |
Online Access: | https://www.journals.vu.lt/LMR/article/view/32273 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Making Virtual Learning Environment more intelligent: the problem of software agent’s mental state recognition
by: Dalia Baziukaitė
Published: (2005-12-01) -
Bayesian Q learning method with Dyna architecture and prioritized sweeping
by: Jun YU, et al.
Published: (2013-11-01) -
Transmission scheduling scheme based on deep Q learning in wireless network
by: Jiang ZHU, et al.
Published: (2018-04-01) -
Virtual Learning Environments from localization point of view
by: Valentina Dagienė, et al.
Published: (2005-12-01) -
Adaptive pilot design for OFDM based on deep reinforcement learning
by: Qiaoshou LIU, et al.
Published: (2023-09-01)