Abstract
In this position paper we propose the approach to use “Thinking-Understanding” architecture for the management of the real-time operated robotic system. Based on the “Robot dream” architecture, the robotic system digital input is been translated in form of “pseudo-spikes” and provided to a simulated spiking neural network, then elaborated and fed back to a robotic system as updated behavioural strategy rules. We present the reasoning rule-based system for intelligent spike processing translating spikes into software actions or hardware signals is thus specified. The reasoning is based on pattern matching mechanisms that activates critics that in their turn activates other critics or ways to think inherited from the work of Marvin Minsky “The emotion machine” [7].
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Acknowledgments
This work was funded by the subsidy allocated to Kazan Federal University for the state assignment in the sphere of scientific activities, grant agreement no. 1.2368.2017; by the subsidy of the Russian Government to support the Program of competitive growth of Kazan Federal University among world class academic centers and universities.
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Toschev, A., Talanov, M., Kurnosov, V. (2018). “Thinking-Understanding” Approach in Spiking Reasoning System. In: Jezic, G., Kusek, M., Chen-Burger, YH., Howlett, R., Jain, L. (eds) Agent and Multi-Agent Systems: Technology and Applications. KES-AMSTA 2017. Smart Innovation, Systems and Technologies, vol 74. Springer, Cham. https://doi.org/10.1007/978-3-319-59394-4_17
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DOI: https://doi.org/10.1007/978-3-319-59394-4_17
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