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george-skal
george-skal commented Jun 28, 2021

Hi all!
I am trying a self-play based scheme, where I want to have two agents in waterworld environment have a policy that is being trained (“shared_policy_1”) and other 3 agents that sample a policy from a menagerie (set) of the previous policies of the first two agents ( “shared_policy_2”).
My problem is that I see that the weights in the menagerie are overwritten in every iteration by the cur

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

  • Updated Jun 8, 2021
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