An Algebraic Notion of Conditional Independence, and its Application to Knowledge Representation

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An Algebraic Notion of Conditional Independence, and its Application to Knowledge Representation

Vortrag von Jesse Heyninck
Conditional independence is a crucial concept supporting adequate modelling and efficient reasoning in probabilistics. In knowledge representation, the idea of conditional independence has also been introduced for specific formalisms, such as propositional logic and belief revision. In this talk, I show how the notion of conditional independence can be studied in the algebraic framework of approximation fixpoint theory. This gives a language-independent account of conditional independence that can be straightforwardly applied to any logic with fixpoint semantics. It is shown how this notion allows to reduce global reasoning to parallel instances of local reasoning. Furthermore, relations to existing notions of conditional independence are discussed and the framework is applied to normal logic programming and abstract dialectical frameworks.