| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0519795 |
| utime |
20241106135817.4 |
| mtime |
20200115235959.9 |
| SCOPUS |
85081588754 |
| WOS |
000507495600041 |
| DOI |
10.1016/j.ifacol.2019.12.656 |
| title
(primary) (eng) |
Preference Elicitation within Framework of Fully Probabilistic Design of Decision Strategies |
| specification |
| page_count |
6 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0519794 |
| ISSN |
2405-8963 |
| title
|
IFAC-PapersOnLine. Volume 52, Issue 29 - Proceedings of the 13th IFAC Workshop on Adaptive and Learning Control Systems 2019 |
| page_num |
239-244 |
| publisher |
| place |
Amsterdam |
| name |
Elsevier |
| year |
2019 |
|
|
| keyword |
dynamic decision making |
| keyword |
Kullback Leibler Divergence |
| keyword |
decision strategy |
| keyword |
fully probabilistic design |
| keyword |
preference elicitation |
| author
(primary) |
| ARLID |
cav_un_auth*0101124 |
| name1 |
Kárný |
| name2 |
Miroslav |
| institution |
UTIA-B |
| full_dept (cz) |
Adaptivní systémy |
| full_dept (eng) |
Department of Adaptive Systems |
| department (cz) |
AS |
| department (eng) |
AS |
| 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 |
| institution |
UTIA-B |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0372050 |
| project_id |
LTC18075 |
| agency |
GA MŠk |
| country |
CZ |
|
| project |
| ARLID |
cav_un_auth*0372051 |
| project_id |
CA16228 |
| agency |
EU-COST |
| country |
XE |
|
| abstract
(eng) |
The paper proposes the preference-elicitation support within the framework of fully probabilistic design (FPD) of decision strategies. Agent employing FPD uses probability densities to model the\nclosed-loop behaviour, i.e. a collection of all observed, opted and considered random variables. Opted actions are generated by a randomised strategy. The optimal decision strategy minimises KullbackLeibler divergence of the closed-loop model to its ideal counterpart describing the agent’s preferences. Thus, selecting the ideal closed-loop model comprises preference elicitation.\nThe paper provides a general choice of the best ideal closed-loop model reflecting agent’s preferences. The foreseen application potential of such a preference elicitation is high as FPD is a non-trivial dense extension of Bayesian decision making that dominates prescriptive decision theories. The general solution is illustrated on the regulation task with a linear Gaussian model describing the agent’s environment. |
| action |
| ARLID |
cav_un_auth*0387490 |
| name |
IFAC Workshop on Adaptive and Learning Control Systems 2019 /13./ |
| dates |
20191204 |
| mrcbC20-s |
20191206 |
| place |
Winchester |
| country |
GB |
|
| RIV |
BD |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2020 |
| mrcbC52 |
4 A sml 4as 20241106135817.4 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0304785 |
| confidential |
S |
| contract |
| name |
Copyright form |
| date |
20191107 |
|
| mrcbC86 |
n.a. Proceedings Paper Automation Control Systems |
| mrcbT16-s |
0.260 |
| mrcbT16-E |
Q3 |
| arlyear |
2019 |
| mrcbTft |
\nSoubory v repozitáři: karny-0519795 -ALCOS19_CopyrightForm_57.pdf |
| mrcbU14 |
85081588754 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000507495600041 WOS |
| mrcbU63 |
cav_un_epca*0519794 IFAC-PapersOnLine. Volume 52, Issue 29 - Proceedings of the 13th IFAC Workshop on Adaptive and Learning Control Systems 2019 2405-8963 239 244 Amsterdam Elsevier 2019 |
|