Construct · 1 fields · 1 citations

non-stationarity in multi-agent learning: a standalone construct

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Multi-agent systems

each agent's environment keeps changing because other agents are learning too, which breaks the stationarity assumptions of single-agent methods.

In multi-agent systems, non-stationarity in multi-agent learning refers to each agent's environment keeps changing because other agents are learning too, which breaks the stationarity assumptions of single-agent methods. This meaning comes from Hernandez-Leal (2017) in arXiv.[1]

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Nearby constructs

agent3 fields · 5 citationsjingle · one word, three constructs environment1 fields · 2 citationsanchor · a standalone construct learning6 fields · 14 citationsjingle · one name, six constructs

References

Hernandez-Leal, P., Kaisers, M., Baarslag, T., & de Cote, E. M. (2017). A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity. arXiv. https://doi.org/10.48550/arxiv.1707.09183

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