What exactly are the differences in centralized and decentralized training for multi agent reinforcement learning? Is centralized learning the same as the paradigm of CTDE (centralized training and decentralized execution) that is seen in much of the multi agent RL literature? When I run centralized training , the main difference I notice is that it appears that all agents are receiving the same Q0 value, which I believe means they have the same critic. I see that both methods are used in the tutorials, so I’m trying to get a clearer picture of what the differences are and when to use one versus the other.What exactly are the differences in centralized and decentralized training for multi agent reinforcement learning? Is centralized learning the same as the paradigm of CTDE (centralized training and decentralized execution) that is seen in much of the multi agent RL literature? When I run centralized training , the main difference I notice is that it appears that all agents are receiving the same Q0 value, which I believe means they have the same critic. I see that both methods are used in the tutorials, so I’m trying to get a clearer picture of what the differences are and when to use one versus the other. What exactly are the differences in centralized and decentralized training for multi agent reinforcement learning? Is centralized learning the same as the paradigm of CTDE (centralized training and decentralized execution) that is seen in much of the multi agent RL literature? When I run centralized training , the main difference I notice is that it appears that all agents are receiving the same Q0 value, which I believe means they have the same critic. I see that both methods are used in the tutorials, so I’m trying to get a clearer picture of what the differences are and when to use one versus the other. reinforcement learning MATLAB Answers — New Questions

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