Comparing search algorithms on the retrosynthesis problem

Abstract: In this article we try different algorithms, namely Nested Monte Carlo Search and Greedy Best First Search, on AstraZeneca's open source retrosynthetic tool: AiZynthFinder. We compare these algorithms to AiZynthFinder's base Monte Carlo Tree Search on a benchmark selected from the PubChem database and by Bayer's chemists. We show that both Nested Monte Carlo Search and Greedy Best First Search outperform AstraZeneca's Monte Carlo Tree Search, with a slight advantage for Nested Monte Carlo Search while experimenting on a playout heuristic. We also show how the search algorithms are bounded by the quality of the policy network, in order to improve our results the next step is to improve the policy network.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Comparing search algorithms on the retrosynthesis problem ; day:12 ; month:06 ; year:2024 ; extent:12
Molecular informatics ; (12.06.2024) (gesamt 12)

Creator
Roucairol, Milo
Cazenave, Tristan

DOI
10.1002/minf.202300259
URN
urn:nbn:de:101:1-2406131407426.801440321574
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:59 AM CEST

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Associated

  • Roucairol, Milo
  • Cazenave, Tristan

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