HQ-Learning

HQ-Learning (1997)

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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}
}

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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.

Citations

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