MERGING OF DATA KNOWLEDGE IN BAYESIAN ESTIMATION

Jan Kracík, Miroslav Kárný

2005

Abstract

Efficient multiple participant decision-making relies on cooperation of participants. Partially, it is reached by sharing knowledge. A specific but important case of this type is addressed here. Essentially, a participant passes to its partner distribution on common data and partner uses it for correcting its Bayesian parameter estimate.

Paper Citation

in Harvard Style

Kracík J. and Kárný M. (2005). MERGING OF DATA KNOWLEDGE IN BAYESIAN ESTIMATION . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 972-8865-31-7, pages 229-232. DOI: 10.5220/0001174502290232

in Bibtex Style

@conference{icinco05,
author={Jan Kracík and Miroslav Kárný},
title={MERGING OF DATA KNOWLEDGE IN BAYESIAN ESTIMATION},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2005},
pages={229-232},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001174502290232},
isbn={972-8865-31-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - MERGING OF DATA KNOWLEDGE IN BAYESIAN ESTIMATION
SN - 972-8865-31-7
AU - Kracík J.
AU - Kárný M.
PY - 2005
SP - 229
EP - 232
DO - 10.5220/0001174502290232