Hertzberg, J, Zhang, J, Zhang, L et al. (18 more authors) (2014) The RACE Project: Robustness by Autonomous Competence Enhancement. KI - Künstliche Intelligenz, 28 (4). pp. 297-304. ISSN 0933-1875
Abstract
This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer-Verlag Berlin Heidelberg 2014. This is an author produced version of a paper published in KI - Künstliche Intelligenz. The final publication is available at Springer via http://dx.doi.org/10.1007/s13218-014-0327-y. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Task Plan; Feature Extraction; Compositional Hierarchy; Constraint Satisfaction Problem; Action Primitive; Conceptual Knowledge; Robot Behavior; Object Category; Hybrid Reasoning; Plan Generation; Ego Network; Graph Similarity; Plan Execution; Object Perception; Planning Domain |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Funding Information: | Funder Grant number EU - European Union 287752 |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 May 2016 12:13 |
Last Modified: | 21 Jan 2018 13:40 |
Published Version: | http://dx.doi.org/10.1007/s13218-014-0327-y |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/s13218-014-0327-y |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:96959 |