Mol-DQN

Optimization of Molecules via Deep Reinforcement Learning https://arxiv.org/abs/1810.08678

##Model

1). logP

• reward : penalized logP
• ./models/logp_model/train.py

2). QED

• reward : QED(Quantitative Estimate of Druglikeness)
• ./models/qed_model/train.py

3). logP_constraint

• reward : logP - w*(k-similarity)
• ./models/logP_constraint/train.py

4). multiobjective

• reward : w*similarity + (1-w)*QED
• ./models/multi_logp_qed_model/train.py

##Result