Adaptive Elicitation of Preferences Under Uncertainty in Sequential Decision Making Problems
Abstract
This paper aims to introduce an adaptive preference elicitation method for interactive decision support in sequential decision problems. The Decision Maker's preferences are assumed to be representable by an additive utility, initially unknown or imperfectly known. We first study the determination of possibly optimal policies when admissible utilities are imprecisely defined by some linear constraints derived from observed preferences. Then, we introduce a new approach interleaving elicitation of utilities and backward induction to incrementally determine an optimal or near-optimal policy. We propose an interactive algorithm with performance guarantees and describe numerical experiments demonstrating the practical efficiency of our approach.
Cite
Text
Benabbou and Perny. "Adaptive Elicitation of Preferences Under Uncertainty in Sequential Decision Making Problems." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/637Markdown
[Benabbou and Perny. "Adaptive Elicitation of Preferences Under Uncertainty in Sequential Decision Making Problems." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/benabbou2017ijcai-adaptive/) doi:10.24963/IJCAI.2017/637BibTeX
@inproceedings{benabbou2017ijcai-adaptive,
title = {{Adaptive Elicitation of Preferences Under Uncertainty in Sequential Decision Making Problems}},
author = {Benabbou, Nawal and Perny, Patrice},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2017},
pages = {4566-4572},
doi = {10.24963/IJCAI.2017/637},
url = {https://mlanthology.org/ijcai/2017/benabbou2017ijcai-adaptive/}
}