MERGING OF DATA KNOWLEDGE IN BAYESIAN ESTIMATION

Jan Kracík, Miroslav Kárný

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.

References

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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