Optimization of Molecules via Deep Reinforcement Learning
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DOI: 10.1038/s41598-019-47148-x
Abstract: 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). We directly define modifications… read more here.
Keywords: optimization molecules; chemistry; reinforcement learning; optimization ... See more keywords