bibtype J - Journal Article
ARLID 0339283
utime 20240103193131.4
mtime 20100224235959.9
title (primary) (eng) Cooperation via sharing of probabilistic information
specification
page_count 24 s.
serial
ARLID cav_un_epca*0339445
ISSN 1755-4977
title International Journal of Computational Intelligence Studies
page_num 139-162
keyword Bayesian decision making
keyword multiple participant
keyword decision making
author (primary)
ARLID cav_un_auth*0101124
name1 Kárný
name2 Miroslav
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*0101092
name1 Guy
name2 Tatiana Valentine
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.
author
ARLID cav_un_auth*0205835
name1 Bodini
name2 A.
country IT
author
ARLID cav_un_auth*0205836
name1 Ruggeri
name2 F.
country IT
source
url http://library.utia.cas.cz/separaty/2010/AS/karny-cooperation via sharing of probabilistic information.pdf
cas_special
project
project_id GA102/08/0567
agency GA ČR
ARLID cav_un_auth*0239566
project
project_id 2C06001
agency GA MŠk
ARLID cav_un_auth*0217685
research CEZ:AV0Z10750506
abstract (eng) The paper concerns a cooperation problem in multiple participant decision making (DM). A fully scalable cooperation model with individual participants being Bayesian decision makers who use fully probabilistic design of the optimal decision strategy is presented. The solution suggests a flat structure of cooperation, where each participant interacts with several ‘neighbours’. The cooperation consists in providing probabilistic distributions a participant uses for its DM. The group DM is then determined by a way of exploitation of the offered non-standard (probabilistic) fragmental information. The paper proposes a systematic procedure by formulating and solving the exploitation problem in a Bayesian way.
reportyear 2010
RIV BB
permalink http://hdl.handle.net/11104/0182856
arlyear 2009
mrcbU63 cav_un_epca*0339445 International Journal of Computational Intelligence Studies 1755-4977 Vol. 1 No. 2 2009 139 162