An ontology-based multi-level robot architecture for learning from experiences

S. Rockel, B. Neumann, J. Zhang, K. S.R. Dubba, A. G. Cohn, Š Konečný, M. Mansouri, F. Pecora, A. Saffiotti, M. Günther, S. Stock, J. Hertzberg, A. M. Tomé, A. Pinho, L. Seabra Lopes, S. Von Riegen, L. Hotz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Citations (Scopus)


One way to improve the robustness and flexibility of robot performance is to let the robot learn from its experiences. In this paper, we describe the architecture and knowledge-representation framework for a service robot being developed in the EU project RACE, and present examples illustrating how learning from experiences will be achieved. As a unique innovative feature, the framework combines memory records of low-level robot activities with ontology-based high-level semantic descriptions.

Original languageEnglish
Title of host publicationDesigning Intelligent Robots
Subtitle of host publicationReintegrating AI II - Papers from the AAAI Spring Symposium
PublisherAAAI Press
ISBN (Print)9781577356011
Publication statusPublished - 15 Mar 2013
Event2013 AAAI Spring Symposium - Palo Alto, CA, United States
Duration: 25 Mar 201327 Mar 2013

Publication series

NameAAAI Spring Symposium Series
PublisherAAAI Press


Conference2013 AAAI Spring Symposium
Country/TerritoryUnited States
CityPalo Alto, CA

ASJC Scopus subject areas

  • Artificial Intelligence


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