[Computer-go] Neural networks + MCTS applied to chemical syntheses

[Fidel Santiago]

Hello,

Apparently the lessons of Alphago (and many others) are being applied to other fields:

https://www.nature.com/articles/d41586-018-03774-5

"The authors devised a computational process that starts by automatically extracting chemical transformations from a large commercial database, being careful to include only reactions that have been reported several times. Their system accepts these well-precedented reactions as ‘allowed moves’ in organic synthesis. When the system is asked to devise a synthetic route to a target molecule, it works backwards from the target as would a human, picking out the most promising precursor molecules according to the design rules that it has learnt, and then seeing how feasible it is to synthesize those. The authors combined three artificial neural networks with a random Monte Carlo tree search — a type of search algorithm used by computers in certain decision-making processes — to narrow down the most promising synthetic routes, without getting stuck too quickly on a particular path."

Ciao!

Fidel Santiago.

[Brian Lee]

In particular, they had no way to train a value net, so it was back to AlphaGo v1 style of training just a policy net and reusing it as the rollout policy.

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