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

[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.



On Fri, Apr 6, 2018 at 6:31 AM Fidel Santiago  wrote:

> 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.
> ___
> Computer-go mailing list
> Computer-go@computer-go.org
> http://computer-go.org/mailman/listinfo/computer-go
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

[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.
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go