# Can alpha-beta pruning be used for applications apart from games?

Can alpha-beta pruning/ minimax be used for systems apart from games? Like for selecting the right customer for a product, etc. (the typical data science problems)? I have seen people do it, but can't understand how. Can someone help me understand that?

Can I do something like if - find two criteria on which customers can buy product depends on like gender and age. Find the probability for all the customers depending on age and gender if they can buy it.

like if there are 3 customers - there probability to buy a product on the basis of their age and gender is - Customer 1 - (20%, 30%), Customer 2 - (30%, 60%), Customer 3 - (40%, 20%). here the x and y represents - (probability based on age, probability based on gender ). Probability is probability to buy the product.

For minimax, will it be correct if one player(max) tries to select the customer on basis of gender and other player(min) on basis of age. so, one can be max and one can be min.

Dont know if this correct or not, but just a idea.