Sökning: L773:9798350336702 OR L773:9798350336719 > Robot causal discov...
Fältnamn | Indikatorer | Metadata |
---|---|---|
000 | 03092naa a2200385 4500 | |
001 | oai:DiVA.org:umu-219029 | |
003 | SwePub | |
008 | 240105s2023 | |||||||||||000 ||eng| | |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-2190292 URI |
024 | 7 | a https://doi.org/10.1109/RO-MAN57019.2023.103093762 DOI |
040 | a (SwePub)umu | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a ref2 swepub-contenttype |
072 | 7 | a kon2 swepub-publicationtype |
100 | 1 | a Edström, Filip,d 1991-u Umeå universitet,Statistik4 aut0 (Swepub:umu)fied0002 |
245 | 1 0 | a Robot causal discovery aided by human interaction |
264 | 1 | b IEEE,c 2023 |
338 | a print2 rdacarrier | |
520 | a Causality is relatively unexplored in robotics even if it is highly relevant, in several respects. In this paper, we study how a robot’s causal understanding can be improved by allowing the robot to ask humans causal questions. We propose a general algorithm for selecting direct causal effects to ask about, given a partial causal representation (using partially directed acyclic graphs, PDAGs) obtained from observational data. We propose three versions of the algorithm inspired by different causal discovery techniques, such as constraint-based, score-based, and interventions. We evaluate the versions in a simulation study and our results show that asking causal questions improves the causal representation over all simulated scenarios. Further, the results show that asking causal questions based on PDAGs discovered from data provides a significant improvement compared to asking questions at random, and the version inspired by score-based techniques performs particularly well over all simulated experiments. | |
650 | 7 | a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Robotteknik och automation0 (SwePub)202012 hsv//swe |
650 | 7 | a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Robotics0 (SwePub)202012 hsv//eng |
650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng |
650 | 7 | a NATURVETENSKAPx Matematikx Sannolikhetsteori och statistik0 (SwePub)101062 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Mathematicsx Probability Theory and Statistics0 (SwePub)101062 hsv//eng |
653 | a human-robot-interaction (hri) | |
653 | a causal discovery | |
653 | a causal inference | |
700 | 1 | a Hellström, Thomasu Umeå universitet,Institutionen för datavetenskap4 aut0 (Swepub:umu)thhe0001 |
700 | 1 | a de Luna, Xavier,c Professoru Umeå universitet,Statistik4 aut0 (Swepub:umu)xade0001 |
710 | 2 | a Umeå universitetb Statistik4 org |
773 | 0 | t 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)d : IEEEg , s. 1731-1736q <1731-1736z 9798350336702z 9798350336719 |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-219029 |
856 | 4 8 | u https://doi.org/10.1109/RO-MAN57019.2023.10309376 |
Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.