Empirical evaluation methods for multiobjective reinforcement learning algorithms

Vamplew, Peter, Dazeley, Richard, Berry, Adam, Issabekov, Rustam and Dekker, Evan 2011, Empirical evaluation methods for multiobjective reinforcement learning algorithms, Machine learning, vol. 84, no. 1-2, pp. 51-80, doi: 10.1007/s10994-010-5232-5.

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Title Empirical evaluation methods for multiobjective reinforcement learning algorithms
Author(s) Vamplew, Peter
Dazeley, RichardORCID iD for Dazeley, Richard orcid.org/0000-0002-6199-9685
Berry, Adam
Issabekov, Rustam
Dekker, Evan
Journal name Machine learning
Volume number 84
Issue number 1-2
Start page 51
End page 80
Total pages 30
Publisher Springer
Place of publication New York, N.Y.
Publication date 2011-07
ISSN 0885-6125
1573-0565
Keyword(s) Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science
Multiobjective reinforcement learning
Multiple objectives
Empirical methods
Pareto fronts
Pareto optimal policies
Language eng
DOI 10.1007/s10994-010-5232-5
Field of Research 0801 Artificial Intelligence And Image Processing
1702 Cognitive Science
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2010, The Author(s)
Persistent URL http://hdl.handle.net/10536/DRO/DU:30113754

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