HQ-Learning (1997)
by
Marco Wiering
,
Jürgen Schmidhuber
| Venue: | ADAPTIVE BEHAVIOR |
| Citations: | 20 - 1 self |
BibTeX
@ARTICLE{Wiering97hq-learning,
author = {Marco Wiering and Jürgen Schmidhuber},
title = {HQ-Learning},
journal = {ADAPTIVE BEHAVIOR},
year = {1997},
volume = {6},
number = {2},
pages = {219--246}
}
Years of Citing Articles
OpenURL
Abstract
HQ-learning is a hierarchical extension of Q()-learning designed to solve certain types of partially observable Markov decision problems (POMDPs). HQ automatically decomposes POMDPs into sequences of simpler subtasks that can be solved by memoryless policies learnable by reactive subagents. HQ can solve partially observable mazes with more states than those used in most previous POMDP work.







