The green nodes represent Q-states, where an action has been taken from a state but has yet to be resolved into a successor state. It’s important to understand that agents spend zero timesteps in Q-states, and that they are simply a construct created for ease of representation and development of MDP algorithms.
→ So Q-state is basically the probability of what the next state will be after taking a certain action.
Finite Horizon is setting finite steps ($m$) an agent can take.
Discounting Factor $\gamma$ is an exponential decay in the value of rewards over time.