Heuristics for spatial data descriptions in a multi-Agent system
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10252541" target="_blank" >RIV/61989100:27240/23:10252541 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/61989100:27350/23:10252541
Výsledek na webu
<a href="https://ebooks.iospress.nl/doi/10.3233/FAIA220493" target="_blank" >https://ebooks.iospress.nl/doi/10.3233/FAIA220493</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/FAIA220493" target="_blank" >10.3233/FAIA220493</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Heuristics for spatial data descriptions in a multi-Agent system
Popis výsledku v původním jazyce
Navigation and an agent's map representation in a multi-Agent system become problematic when agents are situated in complex environments such as the real world. Challenging modifiability of maps, long updating period, resource-demanding data collection makes it difficult for agents to keep pace with rather quickly expanding cities. This study presents the first steps to a possible solution by exploiting natural language processing and symbolic methods of supervised machine learning. An adjusted algorithm processes formalized descriptions of one's journey to produce a description of the journey. The explication is represented employing Transparent Intensional Logic. A combination of several explications might be used as a representation of spatial data, which may help the agents to navigate. Results of the study showed that it is possible to obtain a topological representation of a map using natural language descriptions. Collecting spatial data from spoken language may accelerate updating and creation of maps, which would result in up-To-date information for the agents obtained at a rather low cost. (C) 2023 The authors and IOS Press.
Název v anglickém jazyce
Heuristics for spatial data descriptions in a multi-Agent system
Popis výsledku anglicky
Navigation and an agent's map representation in a multi-Agent system become problematic when agents are situated in complex environments such as the real world. Challenging modifiability of maps, long updating period, resource-demanding data collection makes it difficult for agents to keep pace with rather quickly expanding cities. This study presents the first steps to a possible solution by exploiting natural language processing and symbolic methods of supervised machine learning. An adjusted algorithm processes formalized descriptions of one's journey to produce a description of the journey. The explication is represented employing Transparent Intensional Logic. A combination of several explications might be used as a representation of spatial data, which may help the agents to navigate. Results of the study showed that it is possible to obtain a topological representation of a map using natural language descriptions. Collecting spatial data from spoken language may accelerate updating and creation of maps, which would result in up-To-date information for the agents obtained at a rather low cost. (C) 2023 The authors and IOS Press.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Frontiers in Artificial Intelligence and Applications. Volume 364
ISBN
978-1-64368-370-6
ISSN
0922-6389
e-ISSN
1535-6698
Počet stran výsledku
13
Strana od-do
68-80
Název nakladatele
IOS Press
Místo vydání
Amsterdam
Místo konání akce
Hamburk
Datum konání akce
30. 5. 2022
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—