Abstract
The paper considers an approach to improving the stability of a cognitive agent functioning in hard real time in the event of anomalous situations (anomalies) associated with its functioning. The approach is based on the concept of metacognition (metareasoning) and is implemented by means of Active Logic. The principle of metacognition is based on a metacognitive cycle that includes stages of self-observation (introspection), self-evaluation and self-improvement. Introduces the concept of multiple granulation of time, when each inference step of the agent corresponds to the individual temporal granules and these granules are different for the various inference steps. It is shown that in some cases multiple granulation of time contributes to the timely detection of anomalies.
This work was supported by the Russian Foundation for Basic Research (RFBR) (projects 19-07-00439, 19-07-00-123, 17-07-00696, 18-07-00213, 18-51-00007, 18-29-03088, 17-07-01374).
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Vinkov, M., Fominykh, I., Alekseev, N. (2020). Detection of Anomalous Situations in an Unforeseen Increase in the Duration of Inference Step of the Agent in Hard Real Time. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_18
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