You have to make what seems to be a simple decision... what is the right price for your product? What is the best technology for a job?  

Perhaps you are designing a new material where you want to maximize strength. You have to play with temperatures, concentrations, and ratios.

Or you are trying to optimize the performance of a company through expensive computer simulations. You can tune fleet sizes and inventories, locations of facilities, and the type of equipment you are using.

Optimal learning allows business to make these decisions in minimal time with minimal costs.

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Optimal learning guides the process of collecting information efficiently in order to provide the greatest possible value. It leverages the knowledge of experienced professionals, and works in an interactive fashion to guide the experimental process using a powerful concept called the knowledge gradient which captures the value of information.  


 

KG "Road Map"

Do we explore? The KG map shows where we will learn the most.

Current Estimate of Objective

Do we exploit? This is the region where we think we will get the best results (but we might be wrong).


In all of these settings you learn by trial and error, whether it is in the marketplace, a laboratory, or a computer simulation. But experiments can be time consuming and expensive. You need to learn what works best, but you need to learn quickly. You need optimal learning. 

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The flexibility of optimal learning allows us to handle almost any problem. From improving the process of RNA characterization, testing business decisions, or managing high value spare parts, optimal learning can optimize almost any problem your business can throw at it. 

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