Completeness and Diversity in Depth-First Proof-Number Search with Applications to Retrosynthesis

Abstract

We revisit Depth-First Proof-Number Search (DFPN), a well-known algorithm for solving two-player games. First, we consider the completeness property of the algorithm and its variants, i.e., whether they always find a winning strategy when there exists one. While it is known that the standard version is not complete, we show that the combination with the simple Threshold Controlling Algorithm is complete, solving an open problem from the area. Second, we modify DFPN to compute a diverse set of solutions rather than just a single one. Finally, we apply this new variant in Chemistry to the synthesis planning of new target molecules (Retrosynthesis). In this domain a diverse set of many solutions is desirable. We apply additional modifications from the literature to the algorithm and show that it outperforms Monte-Carlo Tree-Search, another well-known algorithm for the same problem, according to a natural diversity measure.