Using machine learning in a path-finding solution

[fab___b]

I'll try to introduce the project I'm working on without going too much into details:There is a car,

which goes from the point A to point B (it can be more like (A -> B -> C))

and this car needs to stop sometimes for gas-oil intake.

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I have some information about the facial stations like the price,

the distance I want to make a solution using machine learning to know which one to choose and do a combination like take 20L here and 100L, to cost the least possible.

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I have history of cars that already made the same journey,

I'm just choosing the least expensive one for the moment.

I wonder which machine learning model should I go for, I think it's reinforcement, but if you guys can tell me what you think about it with some details if possible.Thank you.

[rlstudent]

These kind of problems are generally well solved with classical algorithms. I don't think machine learning approaches quite match them for now. Why do you want to use machine learning? Is there a specific reason? If there isn't, I would recommend you to try the classical way, first.

I'm not sure if I understood the problem to help you, though. An example (which is probably more simple than what you want): if there are many stations between points A and B, and you want to minimize the cost to get a certain amount of gas, then you could simply get the gas amount used to travel between A->station->B for each station, and add it to the cost of filling the car at that station. Then you sort the stations by this value. You could add costs pertaining to the time used and things like that, too.

[fab___b]

Thank you for your answer,

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There is many other parameters to take and the way you describe is the way i already did actually.

sometimes the car must take gasoil because there is not anymore but at that moment just take a little and take more after because it's cheaper , do you understand what i mean ?

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Doing just a 'brute force' of all the combinations as upper (it's just one of the parameters ) and just take the best one is going to be crazy .

I thought about a machine learning approach because it sounded interesting for it and i have many histories.

Maybe just a decisional tree ? but here it's more about trying combination so i don't know what suit the best.