Optimization of Molecules via Deep Reinforcement Learning

7 code implementations • 19 Oct 2018 • Zhenpeng Zhou, Steven Kearnes, Li Li, Richard N. Zare, Patrick Riley

We present a framework, which we call Molecule Deep $Q$-Networks (MolDQN), for molecule optimization by combining domain knowledge of chemistry and state-of-the-art reinforcement learning techniques (double $Q$-learning and randomized value functions).

Molecular Graph Generation Multi-Objective Reinforcement Learning +2