# Approximate value iteration for continuous state space MDPs

I have a continuous state space MDP as a generative model. I input the state and action and it outputs the reward and the next state. Assume that I sampled $n$ state-reward-states. I wonder how I can implement value iteration using a function approximator. I couldn't find any implementation example online. Can you please point me some references?