I would like the community to help me understand if the following example would be better represented as episodic or continuous task, this will help me structure the problem and chose the right RL algorithm.
The agent start with an initial score
x of let's say 100. The agent objective is to maximise it's score. There is no upper bound! Theoretically the agent can get a score up to infinity, and there is no termination based on the number of steps, therefore the agent could play forever. However, the score can't be negative and if the agent get to a score of zero, the episode should terminate and the environment reset. I am undecided what would be the best representation, because if the agent learns how to play, the episode would never terminate, and the agent would theoretically play forever. However if the score get to zero, there is no way for the agent to continue playing so the environment needs to reset. Thank you.