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3 votes
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What modifications can maximize the efficacy of the REINFORCE algorithm for a policy gradient task?

One simple improvement over the REINFORCE algorithm you've linked to is to use the advantage function instead of the normalised cumulative discounted return. The implementation is can be found in the ...
2 votes
Accepted

How can rewards and loss calculation be extended to multiple agents in a vanilla policy gradient RL setting?

Yes, this can be done and is widely applied in recent literature on multi-agent RL, at least with the collaborative setting where agents are optimizing a shared reward. This is also known as parameter ...
  • 438
1 vote

How is reinforcement learning applied in the real industry?

RL is not used much in the real industry, as you said because of safety concerns. There are perhaps three different ways of how this would be possible Use safe exploration to learn a model of the ...
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