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

AAAI 2025 · Learning theory and algorithms › Combinatorial and search optimization · approach: Logic and answer set programming theory · 0 citations (OpenAlex)

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Defines an algebraic, operator-based notion of conditional independence for lattices and approximation operators, derives modular fixpoint and FPT results, and applies it to normal logic programs.

Problem

Conditional independence is well studied in probability and for specific KR formalisms (propositional logic, belief revision, conditional logics) but lacks a language-independent operator-based account that enables modular reasoning over fixpoint semantics.

Approach

Define conditional independence of sub-lattices w.r.t. an operator on a product lattice, so the operator decomposes into two component operators over pivot-plus-one-side sub-lattices; lift this to approximation operators and stable/well-founded fixpoints, and organize decompositions into conditional independence trees whose size parametrizes FPT algorithms.

Key results

Surprising findings

Limitations

Experimental setup

Builds on: approximation fixpoint theory stratification in AFT Darwiche's logical conditional independence

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