KR2025Proceedings of the 22nd International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning

Melbourne, Australia. November 11-17, 2025.

Edited by

ISSN: 2334-1033
ISBN: 978-1-956792-08-9

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Copyright © 2025 International Joint Conferences on Artificial Intelligence Organization

Presburger Functional Synthesis: Complexity and Tractable Normal Forms

  1. S. Akshay(Indian Institute of Technology Bombay)
  2. A. R. Balasubramanian(Max Planck Institute for Software Systems Kaiserslautern)
  3. Supratik Chakraborty(Indian Institute of Technology Bombay)
  4. Georg Zetzsche(Max Planck Institute for Software Systems Kaiserslautern)

Keywords

  1. Functional Synthesis
  2. Skolem Functions
  3. Knowledge Representation
  4. Computational Complexity
  5. Quantifier Elimination

Abstract

Given a relational specification between inputs and outputs as a logic formula, the problem of functional synthesis is to automatically synthesize a function from inputs to outputs satisfying the relation. Recently, a rich line of work has emerged tackling this problem for specifications in different theories, from Boolean to general first-order logic. In this paper, we

launch an investigation of this problem for the theory of Presburger Arithmetic, that we call Presburger Functional Synthesis (PFnS). We show that PFnS can be solved in EXPTIME

and provide a matching exponential lower bound. This is unlike the case for Boolean functional synthesis (BFnS), where only conditional exponential lower bounds are known. Further, we show that PFnS for one input and one output variable is as hard as BFnS in general. We then identify a special normal form, called PSyNF, for the specification formula that

guarantees poly-time and poly-size solvability of PFnS. We prove several properties of PSyNF, including how to check and compile to this form, and conditions under which any

other form that guarantees poly-time solvability of PFnS can be compiled in poly-time to PSyNF. Finally, we identify a syntactic normal form that is easier to check but is exponentially less succinct than PSyNF.