TY - GEN
T1 - A communicative robot to learn about us and the world
AU - Vossen, Piek
AU - Baez Santamaria, Selene
AU - Bajc̆etić, Lenka
AU - Bašić, Suzana
AU - Kraaijeveld, Bram
PY - 2019/6
Y1 - 2019/6
N2 - We describe a model for a robot that learns about the world and her com-panions through natural language communication. The model supports open-domain learning, where the robot has a drive to learn about new con-cepts, new friends, and new properties of friends and concept instances. The robot tries to fill gaps, resolve uncertainties and resolve conflicts. The absorbed knowledge consists of everything people tell her, the situations and objects she perceives and whatever she finds on the web. The results of her interactions and perceptions are kept in an RDF triple store to enable reasoning over her knowledge and experiences. The robot uses a theory of mind to keep track of who said what, when and where. Accumulating knowledge results in complex states to which the robot needs to respond. In this paper, we look into two specific aspects of such complex knowl-edge states: 1) reflecting on the status of the knowledge acquired through a new notion of thoughts and 2) defining the context during which knowl-edge is acquired. Thoughts form the basis for drives on which the robot communicates. We capture episodic contexts to keep instances of objects apart across different locations, which results in differentiating the acquired knowledge over specific encounters. Both aspects make the communica-tion more dynamic and result in more initiatives by the robot
AB - We describe a model for a robot that learns about the world and her com-panions through natural language communication. The model supports open-domain learning, where the robot has a drive to learn about new con-cepts, new friends, and new properties of friends and concept instances. The robot tries to fill gaps, resolve uncertainties and resolve conflicts. The absorbed knowledge consists of everything people tell her, the situations and objects she perceives and whatever she finds on the web. The results of her interactions and perceptions are kept in an RDF triple store to enable reasoning over her knowledge and experiences. The robot uses a theory of mind to keep track of who said what, when and where. Accumulating knowledge results in complex states to which the robot needs to respond. In this paper, we look into two specific aspects of such complex knowl-edge states: 1) reflecting on the status of the knowledge acquired through a new notion of thoughts and 2) defining the context during which knowl-edge is acquired. Thoughts form the basis for drives on which the robot communicates. We capture episodic contexts to keep instances of objects apart across different locations, which results in differentiating the acquired knowledge over specific encounters. Both aspects make the communica-tion more dynamic and result in more initiatives by the robot
KW - Knowledge acquisition
KW - Modeling
KW - Multimodal communication
KW - Social robots
UR - http://www.scopus.com/inward/record.url?scp=85079004917&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85079004917&partnerID=8YFLogxK
UR - http://www.dialog-21.ru/en/digest/2019/articles/
UR - http://www.dialog-21.ru/media/4872/_-dialog2019scopus_rev2.pdf
M3 - Conference contribution
AN - SCOPUS:85079004917
T3 - Komp'juternaja Lingvistika i Intellektual'nye Tehnologii - Issues
SP - 728
EP - 743
BT - Computational Linguistics and Intellectual Technologies
CY - Moscow
T2 - 2019 Annual International Conference on Computational Linguistics and Intellectual Technologies, Dialogue 2019
Y2 - 29 May 2019 through 1 June 2019
ER -