In a simulated spasmodic walleye fishery, machine-learned harvest rules beat conventional rules only for trophy fishing, by waiting for big year classes to grow, and mean fish weight helps only in that setting.
Optimal fishery policy: An equilibrium solution with irreversible investment
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Using machine learning to inform harvest control rule design in complex fishery settings
In a simulated spasmodic walleye fishery, machine-learned harvest rules beat conventional rules only for trophy fishing, by waiting for big year classes to grow, and mean fish weight helps only in that setting.