Policy Distillation and Value Matching in Multiagent Reinforcement Learning

Policy Distillation and Value Matching in Multiagent Reinforcement Learning

© 2019 IEEE. Multiagent reinforcement learning (MARL) algorithms have been demonstrated on complex tasks that require the coordination of a team of multiple agents to complete. Existing works have focused on sharing information between agents via centralized critics to stabilize learning or through...

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Bibliographic Details
Main Authors: Wadhwania, Samir, Kim, Dong-Ki, Omidshafiei, Shayegan, How, Jonathan P.
Other Authors: Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Format: Article
Language:English
Published: IEEE 2021
Online Access:https://hdl.handle.net/1721.1/137155

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https://hdl.handle.net/1721.1/137155

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