bibtype G - Proceedings (international conference)
ARLID 0396745
utime 20240103203024.0
mtime 20131003235959.9
ISBN 978-80-903834-8-7
title (primary) (eng) Scalable Decision Making: Uncertainty, Imperfection, Deliberation, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2013)
publisher
place Prague
name ÚTIA AV ČR, v.v.i
pub_time 2013
specification
page_count 112 s.
media_type P
keyword scalable
keyword decision making
keyword uncertainty
keyword imperfection
keyword deliberation
author (primary)
ARLID cav_un_auth*0101092
name1 Guy
name2 Tatiana Valentine
full_dept (cz) Adaptivní systémy
full_dept (eng) Department of Adaptive Systems
department (cz) AS
department (eng) AS
institution UTIA-B
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101124
name1 Kárný
name2 Miroslav
full_dept (cz) Adaptivní systémy
full_dept Department of Adaptive Systems
department (cz) AS
department AS
institution UTIA-B
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
cas_special
project
project_id GA13-13502S
agency GA ČR
ARLID cav_un_auth*0292725
abstract (eng) Machine learning (ML) and knowledge discovery both use and serve to decision making (DM), which has to cope with uncertainty, incomplete knowledge, problem and data complexity and imperfection (limited cognitive and evaluating capabilities) of the involved heterogeneous multiple participants (aka agents, decision makers, components, controllers, classifiers, etc.). Contemporary DM deals with complex systems characterised by heterogeneous components and their goal-motivated dynamic interactions. The individual participants are selfish, i.e. follow their individual goals. There is no well-justified way to influence or describe the resulting collective behaviour of such a system via a well-proved combination of the selfish components. Economic and natural sciences describe concepts governing the functioning of systems of selfish participants as well as ways influencing their behaviour. However, the majority of solutions rely on the human moderator/manager controlling such a system.
action
ARLID cav_un_auth*0294508
name European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDO 2013)
place Prague
dates 23.09.2013-27.09.2013
country CZ
reportyear 2014
RIV BB
num_of_auth 29
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0224479
arlyear 2013
mrcbU10 2013
mrcbU10 Prague ÚTIA AV ČR, v.v.i
mrcbU12 978-80-903834-8-7