Mean field games
PulseAugur coverage of Mean field games — every cluster mentioning Mean field games across labs, papers, and developer communities, ranked by signal.
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New framework for risk-averse multi-population mean-field games introduced
This paper introduces a new framework for risk-averse multi-population mean-field games, designed to model large-scale heterogeneous multi-agent systems. The approach accounts for uncertainty in the behavior of other po…
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New framework learns hidden altruism and cost levels in agent games
Researchers have developed a new inverse learning framework for mixed-individual mean field games (MFGs). This framework aims to recover unobservable parameters like altruism and labor cost levels from noisy observation…
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New AI methods tackle imperfect-information games
Researchers are developing new methods to tackle complex games with imperfect information. One paper introduces Recurrent Structural Policy Gradient (RSPG), a novel approach for partially observable mean field games tha…