Web: http://arxiv.org/abs/2005.13625

Jan. 31, 2022, 2:11 a.m. | J. K. Terry, Nathaniel Grammel, Sanghyun Son, Benjamin Black

cs.LG updates on arXiv.org arxiv.org

Parameter sharing, where each agent independently learns a policy with fully
shared parameters between all policies, is a popular baseline method for
multi-agent deep reinforcement learning. Unfortunately, since all agents share
the same policy network, they cannot learn different policies or tasks. This
issue has been circumvented experimentally by adding an agent-specific
indicator signal to observations, which we term "agent indication." Agent
indication is limited, however, in that without modification it does not allow
parameter sharing to be applied to …

agents arxiv learning reinforcement learning

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