Abstract
The ability to understand why a particular robot behavior was triggered is a cornerstone for having human-acceptable social robots. Every robot action should be able to be explained and audited, expected and unexpected robot behaviors should generate a fingerprint showing the components and events that produce them. This research proposes a three-dimensional model for accountability in autonomous robots. The model shows three different elements that deal with the different levels of information, from low-level such as logging to a high level, such as robot behavior. The model proposes three different approaches of visualization, one on command line and two using GUI. The three-level system allows a better understanding of robot behaviors and simplifies the mapping of observable behaviors with accountable information.
The research described in this article has been partially funded by addendum 4 to the framework convention between the University of León and Instituto Nacional de Ciberseguridad (INCIBE).
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Rodríguez-Lera, F.J., González Santamarta, M.Á., Guerrero, Á.M., Martín, F., Matellán, V. (2021). Traceability and Accountability in Autonomous Agents. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) 13th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2020). CISIS 2019. Advances in Intelligent Systems and Computing, vol 1267. Springer, Cham. https://doi.org/10.1007/978-3-030-57805-3_28
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