[D] Which approach is suitable for solving continuous reinforcment learning tasks? • r/MachineLearning

Hello everyone, I'm currently studying some RL approaches from the well-known book(draft) of Sutton & Barto and have some problems in understanding approaches that solve continuing tasks (/non episodic task). Common algorithms like Q-Learning, Sarsa and Monte Carlo Control seem to require at leat one terminal-state to learn an optimal policy. The question that comes in my mind is, whether those algorithms can also be used for a continuing tasks, which?don't have a final state?.