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DoE Bayesian optimisation

The development of iterative design of experiments based on a Bayesian approach is gaining interest as shown in these two articles:

Shields, B. J., Stevens, J., Li, J., Parasram, M., Damani, F., Alvarado, J. I. M., ... & Doyle, A. G. (2021). Bayesian reaction optimization as a tool for chemical synthesis. Nature590(7844), 89-96.

Greenhill, S., Rana, S., Gupta, S., Vellanki, P., & Venkatesh, S. (2020). Bayesian optimization for adaptive experimental design: a review. IEEE access8, 13937-13948.


A JMP add-in is available to implement this approach (https://community.jmp.com/t5/JMP-Add-Ins/Bayesian-optimization-add-in/ta-p/496785). Unfortunately, the add-in lacks some important features such as:
- the use of several model types (in particular the bootstrap forest)
- the management of discrete variables
- the management of experimental constraints
- the possibility to run several experiments per iteration

 

It would be very appreciable and useful to have such a platform available, especially in the fields of exploratory research for the design of new materials.

 

2 Comments
Status changed to: Acknowledged

Hi @Florent_M, thank you for your suggestion! We have captured your request and will take it under consideration.

SamGardner
Level VII
Status changed to: Investigating

@Florent_M thank you for the suggesting.  We will investigate this further and get back to you when have more information to share.