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KI - Künstliche Intelligenz
Published in: KI - Künstliche Intelligenz 4/2014

01-11-2014 | Research Project

The RACE Project

Robustness by Autonomous Competence Enhancement

Authors: Joachim Hertzberg, Jianwei Zhang, Liwei Zhang, Sebastian Rockel, Bernd Neumann, Jos Lehmann, Krishna S. R. Dubba, Anthony G. Cohn, Alessandro Saffiotti, Federico Pecora, Masoumeh Mansouri, Štefan Konečný, Martin Günther, Sebastian Stock, Luis Seabra Lopes, Miguel Oliveira, Gi Hyun Lim, Hamidreza Kasaei, Vahid Mokhtari, Lothar Hotz, Wilfried Bohlken

Published in: KI - Künstliche Intelligenz | Issue 4/2014

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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.
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Footnotes
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Metadata
Title
The RACE Project
Robustness by Autonomous Competence Enhancement
Authors
Joachim Hertzberg
Jianwei Zhang
Liwei Zhang
Sebastian Rockel
Bernd Neumann
Jos Lehmann
Krishna S. R. Dubba
Anthony G. Cohn
Alessandro Saffiotti
Federico Pecora
Masoumeh Mansouri
Štefan Konečný
Martin Günther
Sebastian Stock
Luis Seabra Lopes
Miguel Oliveira
Gi Hyun Lim
Hamidreza Kasaei
Vahid Mokhtari
Lothar Hotz
Wilfried Bohlken
Publication date
01-11-2014
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 4/2014
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-014-0327-y

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