Detail publikace

Continuous Q-learning application

VĚCHET, S. KREJSA, J.

Anglický název

Continuous Q-learning application

Typ

Stať ve sborníku v databázi WoS či Scopus

Jazyk

en

Originální abstrakt

Standard algorithm of Q-Learning is limited by discrete states and actions and Q-function is usually represented as discrete table. To avoid this obstacle and extend the use of Q-learning for continuous states and actions the algorithm must be modified and such modification is presented in the paper. Straightforward way is to replace discrete table with suitable approximator. A number of approximators can be used, with respect to memory and computational requirements the local approximator is particularly favorable. We have used Locally Weighted Regression (LWR) algorithm. The paper discusses advantages and disadvantages of modified algorithm demonstrated on simple control task.

Klíčová slova anglicky

Q-learning, Machine learning, Locall approximators

Vydáno

2004-05-10

Nakladatel

Institute of Thermonechanics Academy of Sciences of the Czech Republic, Prague 2004

Místo

Prague

ISBN

80-85918-88-9

Kniha

Engineering Mechanics 2004

Strany od–do

307–

Počet stran

2

BIBTEX


@inproceedings{BUT14018,
  author="Stanislav {Věchet} and Jiří {Krejsa}",
  title="Continuous Q-learning application",
  booktitle="Engineering Mechanics 2004",
  year="2004",
  number="1",
  pages="2",
  publisher="Institute of Thermonechanics Academy of Sciences of the Czech Republic, Prague 2004",
  address="Prague",
  isbn="80-85918-88-9"
}