- Title
- An empirical comparison of two common multiobjective reinforcement learning algorithms
- Creator
- Issabekov, Rustam; Vamplew, Peter
- Date
- 2012
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/60825
- Identifier
- vital:4848
- Identifier
-
https://doi.org/10.1007/978-3-642-35101-3_53
- Identifier
- ISBN:03029743 (ISSN); 9783642351006 (ISBN)
- Abstract
- In this paper we provide empirical data of the performance of the two most commonly used multiobjective reinforcement learning algorithms against a set of benchmarks. First, we describe a methodology that was used in this paper. Then, we carefully describe the details and properties of the proposed problems and how those properties influence the behavior of tested algorithms. We also introduce a testing framework that will significantly improve future empirical comparisons of multiobjective reinforcement learning algorithms. We hope this testing environment eventually becomes a central repository of test problems and algorithms The empirical results clearly identify features of the test problems which impact on the performance of each algorithm, demonstrating the utility of empirical testing of algorithms on problems with known characteristics. © 2012 Springer-Verlag.
- Publisher
- Sydney, NSW Springer Berlin Heidelberg
- Relation
- 25th Australasian Joint Conference on Artificial Intelligence, AI 2012 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7691 LNAI, p. 626-636
- Rights
- Copyright 2012 Springer-Verlag
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Learning algorithms
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Published | 285 KB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | SOURCE2 | Accepted version | 387 KB | Adobe Acrobat PDF | View Details Download |