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Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning
Mean Field Games (MFGs) have the ability to handle large-scale multi-agent systems, but learning Nash equilibria in MFGs remains a challenging task.
Learning Correlated Equilibria in Mean-Field Games
The designs of many large-scale systems today, from traffic routing environments to smart grids, rely on game-theoretic equilibrium concepts.
Reinforcement Learning for Mean Field Games, with Applications to Economics
Mean field games (MFG) and mean field control problems (MFC) are frameworks to study Nash equilibria or social optima in games with a continuum of agents.
Mean Field Models to Regulate Carbon Emissions in Electricity Production
The most serious threat to ecosystems is the global climate change fueled by the uncontrolled increase in carbon emissions.
Optimization and Control 49N80, 91A16, 91B76, 49N90, 91A07
