arXiv Open Access 2016

Optimizing Quantiles in Preference-based Markov Decision Processes

Hugo Gilbert Paul Weng Yan Xu

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Abstrak

In the Markov decision process model, policies are usually evaluated by expected cumulative rewards. As this decision criterion is not always suitable, we propose in this paper an algorithm for computing a policy optimal for the quantile criterion. Both finite and infinite horizons are considered. Finally we experimentally evaluate our approach on random MDPs and on a data center control problem.

Topik & Kata Kunci

cs.AI

Penulis (3)

Hugo Gilbert

Paul Weng

Yan Xu

Format Sitasi

APA MLA BibTeX

Gilbert, H., Weng, P., Xu, Y. (2016). Optimizing Quantiles in Preference-based Markov Decision Processes. https://arxiv.org/abs/1612.00094

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Informasi Jurnal

Tahun Terbit: 2016
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓