Forward-looking evolutionary game dynamics are formulated by coupling pairwise comparison protocols with static Hamilton-Jacobi-Bellman equations as a mean field game, with exploration cost incorporated as a constraint via the optimal Lagrangian multiplier, uniqueness shown under conditions, and low
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Musielak-Orlicz spaces enable bounding cumulants in uncertain supOU long-memory processes by state-dependent divergences on reversion and Levy measures, succeeding where Kullback-Leibler fails.
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Forward-looking evolutionary game dynamics subject to exploration cost
Forward-looking evolutionary game dynamics are formulated by coupling pairwise comparison protocols with static Hamilton-Jacobi-Bellman equations as a mean field game, with exploration cost incorporated as a constraint via the optimal Lagrangian multiplier, uniqueness shown under conditions, and low
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A Musielak-Orlicz approach for modeling uncertainties in long-memory processes
Musielak-Orlicz spaces enable bounding cumulants in uncertain supOU long-memory processes by state-dependent divergences on reversion and Levy measures, succeeding where Kullback-Leibler fails.