Quantum-inspired Reinforcement Learning for Synthesizable Drug Design

ArXi:2409.09183v2 Announce Type: replace Synthesizable molecular design (also known as synthesizable molecular optimization) is a fundamental problem in drug discovery, and involves designing novel molecular structures to improve their properties according to drug-relevant oracle functions (i.e., objective) while ensuring synthetic feasibility. However, existing methods are mostly based on random search. To address this issue, in this paper, we