On Discovering Interesting Combinatorial Integer Sequences

On Discovering Interesting Combinatorial Integer Sequences

Martin Svatoš, Peter Jung, Jan Tóth, Yuyi Wang, Ondřej Kuželka

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Main Track. Pages 3338-3346. https://doi.org/10.24963/ijcai.2023/372

We study the problem of generating interesting integer sequences with a combinatorial interpretation. For this we introduce a two-step approach. In the first step, we generate first-order logic sentences which define some combinatorial objects, e.g., undirected graphs, permutations, matchings etc. In the second step, we use algorithms for lifted first-order model counting to generate integer sequences that count the objects encoded by the first-order logic formulas generated in the first step. For instance, if the first-order sentence defines permutations then the generated integer sequence is the sequence of factorial numbers n!. We demonstrate that our approach is able to generate interesting new sequences by showing that a non-negligible fraction of the automatically generated sequences can actually be found in the Online Encyclopaedia of Integer Sequences (OEIS) while generating many other similar sequences which are not present in OEIS and which are potentially interesting. A key technical contribution of our work is the method for generation of first-order logic sentences which is able to drastically prune the space of sentences by discarding large fraction of sentences which would lead to redundant integer sequences.
Keywords:
Knowledge Representation and Reasoning: KRR: Other