I designed the deep reinforcement learning multi-agent system with three DDPG agents. Each agent does an independent task. I prepared a counter to calculate the total rewards of each agent in each episode in the Simulink. The calculated total rewards in each episode for each agent are different from the calculated rewards of each agent in the Matlab training-progress of Reinforcement Learning Episode Manager. But for a single agent in the reinforcement learning system, these rewards were the same.
1) Are the rewards calculated by the algorithm in the multi-agent reinforcement system influenced by the calculations of other agent's rewards?
2) Is the update of the weights of the network of each agent not independent of the other agents?
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