Abstract
Autonomic computing systems maintain high-level goals by continuously adapting to a changing environment, yet their internal operations have no comprehensible meaning to humans. This paper proposes a dialogue management system based on a communication interface acting as a bridge between subsymbolic and symbolic knowledge representation levels. The communication interface explains the autonomic system operation in a human comprehensible form by representing the sensed data in conceptual spaces. Based on a knowledge base generated by the communication interface, the dialogue management system produces a pertinent flow of conversation between autonomic systems and humans, activating only when exceptional situations are encountered. Our approach is incremental, with the objective of enabling pertinent communication with any artificial system. We build a proof-of-concept implementation of the proposed solution in a smart home platform managed by an autonomic system.
M. Pol—Independent researcher.
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Pol, M., Dessalles, JL., Diaconescu, A. (2020). Explanatory AI for Pertinent Communication in Autonomic Systems. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1037. Springer, Cham. https://doi.org/10.1007/978-3-030-29516-5_16
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