| bibtype |
M -
Monography Chapter
|
| ARLID |
0364850 |
| utime |
20240103195603.9 |
| mtime |
20111103235959.9 |
| WOS |
000303779200002 |
| SCOPUS |
84885647522 |
| DOI |
10.1007/978-3-642-24647-0 |
| title
(primary) (eng) |
On Support of Imperfect Bayesian Participants |
| specification |
| page_count |
27 s. |
| book_pages |
210 |
|
| serial |
| ARLID |
cav_un_epca*0364849 |
| ISBN |
978-3-642-24646-3 |
| title
|
Decision Making with Imperfect Decision Makers |
| part_num |
chapter 2 |
| part_title |
On Support of Imperfect Bayesian Participants |
| page_num |
29-56 |
| publisher |
| place |
Berlin Heidelberg |
| name |
Springer |
| year |
2012 |
|
|
| keyword |
Decision Making |
| keyword |
Imperfect Decision Makers |
| keyword |
Intelligent Systems |
| 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. |
|
| source |
|
| cas_special |
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| country |
CZ |
| ARLID |
cav_un_auth*0001814 |
|
| project |
| project_id |
GA102/08/0567 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0239566 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
Bayesian decision theory provides a strong theoretical basis for a singleparticipant decision making under uncertainty, that can be extended to multipleparticipant decision making. However, this theory (similarly as others) assumes unlimited abilities of a participant to probabilistically model the participant’s environment and to optimise its decision-making strategy. The proposed methodology solves knowledge and preference elicitation, as well as sharing of individual, possibly fragmental, knowledge and preferences among imperfect participants. The approach helps to overcome the non-realistic assumption on participants’ unlimited abilities. |
| reportyear |
2012 |
| RIV |
IN |
| mrcbC52 |
4 A 4a 20231122134701.9 |
| permalink |
http://hdl.handle.net/11104/0200225 |
| arlyear |
2012 |
| mrcbTft |
\nSoubory v repozitáři: karny-0364850.pdf |
| mrcbU14 |
84885647522 SCOPUS |
| mrcbU34 |
000303779200002 WOS |
| mrcbU63 |
cav_un_epca*0364849 Decision Making with Imperfect Decision Makers On Support of Imperfect Bayesian Participants chapter 2 978-3-642-24646-3 29 56 Berlin Heidelberg Springer 2012 Intelligent Systems Reference Library Vol. 28 |
|