Citation needed. RL makes sense when you don’t know the dynamics of the environment and have interactions with it. Linear programming can be done when you can

Citation needed. RL makes sense when you don’t know the dynamics of the environment and have interactions with it. Linear programming can be done when you can encode a problem as linear constraints which means you know the dynamics. You can then find the optimal set of points of the convex polyhedron defined by the constraints via interior point methods. That’s it. You don’t need exploration and you can get an optimal solution to the constraints because the feasible space is convex.