Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
Abstract
A detailed analysis of the ECL interaction between luminol and tris(2,2'-bipyridyl)dichlororuthenium(ii) (Ru(bpy)<sub>3</sub><sup>2+</sup>) is required before using them in ECL systems for multianalyte detection purposes. Spectro-electrochemiluminescence demonstrates that not only must the emission properties be considered, but also their additional optical characteristics are involved in the explanation of the interaction mechanism between these luminophores.
Cite
Text
Nikovski and Nourbakhsh. "Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots." International Conference on Machine Learning, 2000.Markdown
[Nikovski and Nourbakhsh. "Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots." International Conference on Machine Learning, 2000.](https://mlanthology.org/icml/2000/nikovski2000icml-learning/)BibTeX
@inproceedings{nikovski2000icml-learning,
title = {{Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots}},
author = {Nikovski, Daniel and Nourbakhsh, Illah R.},
booktitle = {International Conference on Machine Learning},
year = {2000},
pages = {671-678},
url = {https://mlanthology.org/icml/2000/nikovski2000icml-learning/}
}