Wasserstein Lagrangian Mechanics formalizes second-order dynamics in Wasserstein space and provides an algorithm to learn them from observed marginals without specifying the Lagrangian, outperforming gradient flows on various dynamics.
Journal of political economy , volume=
3 Pith papers cite this work. Polarity classification is still indexing.
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HLCP uses N-scaled virtual invariant and trigger-based collateral to reduce LVR, forming a Nash equilibrium and Pareto improvement over standard CPMM in a stylized duopoly under specific conditions.
Using common random numbers in rollout simulations provably reduces variance in relative utility estimates when a rollout policy is invoked beyond some depth.
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Using Common Random Numbers for Simulation-based Planning with Rollouts
Using common random numbers in rollout simulations provably reduces variance in relative utility estimates when a rollout policy is invoked beyond some depth.