We will implement the fitted value iteration algorithm with the following steps:

Step $1$: Discretize the state space into equidistance states $($specifically$,)$;

Step $2$: Approximate the value function by quadratic functions;

Step $3$: Apply gradient descent to update the parameters from value functions, with a learning rate $.$