Researchers Introduce Tree Decision Diagrams as OBDD Extension
Original: A Canonical Generalization of OBDD
Why This Matters
Advances Boolean function representation with improved efficiency for AI reasoning tasks
Computer scientists from multiple institutions introduced Tree Decision Diagrams (TDD), a new model for Boolean functions that generalizes Ordered Binary Decision Diagrams while maintaining tractability properties.
Researchers led by Florent Capelli introduced Tree Decision Diagrams (TDD) as a generalization of Ordered Binary Decision Diagrams (OBDD) for representing Boolean functions. TDDs are positioned as a restriction of structured d-DNNF that respects a vtree structure. The model maintains OBDD's tractability properties including model counting, enumeration, conditioning, and apply operations, while offering improved succinctness. A key finding shows CNF formulas of treewidth k can be represented by TDDs of fixed-parameter tractable size, which is impossible for OBDDs. The research explores compilation complexity of CNF formulas into deterministic TDDs using bottom-up compilation, connecting this complexity to factor width concepts. The work was submitted to SAT26 conference and represents collaboration between researchers from multiple institutions focusing on artificial intelligence and data structures algorithms.
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