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Having only a non-zero reward at the very end is not uncommon. When rewards are sparse, it becomes a bit harder to learn compared to having lots of different rewards along the way, but for your problem, the goal state is always reached, so that should not be a problem. (The real problem with sparse rewards is that, if an agent can do a lot of exploration ...


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If by, I can compute the reward given $(a_1, a_2, \dots, a_n)$ you simply mean that your game is deterministic, this is absolutely fine. I feel another answer had assumed you were implying your terminal reward is a matter of some sequence. RL does, however, struggle more greatly in games with indeterminable reward until the terminal state, however, it is ...


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