Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning

Dong-Ki Kim
Dong-Ki Kim
Sebastian Lopez-Cot
Sebastian Lopez-Cot
Matthew Riemer
Matthew Riemer
Sami Mourad
Sami Mourad

arXiv: Learning, 2019.

Cited by: 3|Bibtex|Views64
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Heterogeneous knowledge naturally arises among different agents in cooperative multiagent reinforcement learning. As such, learning can be greatly improved if agents can effectively pass their knowledge on to other agents. Existing work has demonstrated that peer-to-peer knowledge transfer, a process referred to as action advising, improv...More

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