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Building an explanation generation mechanism in probabilistic knowledge-based systems

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3 Author(s)
Qingmai Wang ; Sch. of Electr. & Comput. Eng., RMIT Univ., Melbourne, VIC, Australia ; Wei Peng ; Xinghuo Yu

This paper proposes a Multiple-run Interactive Certainty Network (MRICN) that integrates human decision-making heuristics into probabilistic approaches for knowledge-based systems. MRICN is built upon ideas drawn from “Opinion Pooling”, “Probabilistic Network” and “Interaction”, allowing for reflective searching for the optimal sets of knowledge with the maximal certainty gain. It is implemented and experimented in an coastal lake sustainability assessment scenario.

Published in:

Industrial Informatics (INDIN), 2010 8th IEEE International Conference on

Date of Conference:

13-16 July 2010