Fuzzy Q-learning

P.Y. Glorennec; L. Jouffe

Found an issue? Give us feedback

https://doi.org/10.1...arrow_drop_down

https://doi.org/10.1109/fuzzy....

Article . 2002 . Peer-reviewed

Data sources: Crossref

https://dx.doi.org/10.1109/fuz...

Other literature type

Data sources: Microsoft Academic Graph

Fuzzy Q-learning

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 22 Nov 2002Publisher:IEEEJournal:Proceedings of 6th International Fuzzy Systems Conference, volume 2, pages 659-662

Authors: P.Y. Glorennec; L. Jouffe;

doi: 10.1109/fuzzy.1997.622790

Fuzzy Q-learning

- Summary
- Metrics

Abstract

This paper proposes an adaptation of Watkins' Q-learning (1989, 1992) for fuzzy inference systems where both the actions and the Q-functions are inferred from fuzzy rules. This approach is compared with genetic algorithm on the cart-centering problem, showing its effectiveness.

Related Organizations

Intelligence and National Security Alliance
United States

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	108
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 1%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%