Bayesian Knowledge Bases
From Distributed Information and Intelligence Analysis Group
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Current revision as of 20:47, 7 August 2009
A Bayesian knowledge-base is a knowledge representation system that has a similar structure as a Bayesian network. It represents knowledge by an “if-then” structure and represents uncertainty by probability theory. BKBs subsume BNs and are advantageous to BNs because BKBs are robust to knowledge incompleteness and cyclic information, while still preserving a probabilistically sound representation of uncertainty. We now extend BKBs to represent both time and interaction since time is the key component of a dynamic world. We target to provide a comprehensive model that can describe the interactions of knowledge in the world, as well as reason through them.
