AICOMay 24

Solving Combinatorial Counting Problems with Weighted First-Order Model Counting

arXiv:2605.2484518.4
AI Analysis

This work provides a unified, automated approach to combinatorial counting for AI and discrete mathematics practitioners, reducing manual effort for problems that previously required ad-hoc methods.

The authors present Cofola, a declarative language for combinatorial counting problems that compiles to weighted first-order model counting, enabling automated solving of problems involving sets, bags, tuples, sequences, circles, partitions, and compositions with constraints. On a suite of representative problems, Cofola produces concise specifications and a practical end-to-end solving pipeline.

Combinatorial counting problems pervade artificial intelligence, statistics, and discrete mathematics. Whether the task is enumerating subsets, multisets, permutations, partitions, or compositions under structural and arithmetic constraints, solving it remains a stubbornly manual exercise. Closed-form derivations are powerful but brittle, while naive encodings to propositional model counting or constraint satisfaction destroy the exchangeability that makes counting tractable in the first place. We present Cofola (COmbinatorial counting LAnguage with First-Order logic), a typed declarative language whose primitives are the combinatorial objects that recur in everyday counting questions, including sets, bags, tuples, sequences, circles, partitions, and compositions, together with natural relational and arithmetic constraints over them. A denotational semantics maps every Cofola program to a well-defined combinatorial counting problem, and a three-phase compilation pipeline (preprocessing, decomposition, and symmetry-preserving encoding) reduces this problem to a weighted first-order model counting (WFOMC) instance augmented with coefficient-extraction constraints. To stay inside known domain-liftable fragments whenever possible, the encoding groups indistinguishable entities, breaks the symmetry of unordered groupings lexicographically, and encodes sequences and circles via order axioms. On a suite of representative combinatorial counting problems, ranging from textbook math problems to multi-object scenarios that the closest prior framework cannot express, Cofola produces concise specifications and a uniform solving pipeline that is practical end-to-end.

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