Hi 郭欣,
As per my understanding, there could be a few potential reasons for the poor performance you’re observing:
- As you mentioned that the training environment is slightly more complex than the validation environment, it is important to have similar complexities between the training and validation to ensure that the trained agents can be generalized.
- Also, to improve the effectiveness of MAPPO, you may want to increase the amount of training data which covers a wide range of scenarios.
- If not, already you may also have to normalize the values to stabilize value learning
- Analysis and refinement of the reward function might also be necessary.
However, it is difficult to pinpoint the exact reason why you are experiencing poor results without looking at your implementation, you can implement a thorough debugging process to track the training progress and identify potential issues.
You can also refer to the following documentation for a better understanding of how to train your reinforcement learning agents
