论文标题
重新审视自适应赌注围场：风险和时间范围的考虑
Adaptive Bet-Hedging Revisited: Considerations of Risk and Time Horizon
论文作者
论文摘要
适应性赌注的模型通常从凯利（Kelly）著名的最佳赌博策略和信息的财务价值中采用见解。特别是，这种模型寻求进化溶液，即使面对高度随机的生长轨迹，也可以最大程度地提高谱系的长期平均生长速率。在这里，我们主张与标准方法广泛不同，以更好地说明进化意外事件。至关重要的是，在有限的时间范围的生长方法中，我们纳入了有限种群中临时灭绝风险的挥发性最小化的考虑。我们发现，游戏理论竞争性的方法最能捕获这些其他限制，并在直接的健身回报功能和灭绝风险下得出了平衡解决方案。我们表明，对于最大生长和最少的相对回报，对数最佳策略是一种独特的纯构策策对对称平衡，不变，并且具有进化的时间范围，并且稳健地降低了灭绝风险。
Models of adaptive bet-hedging commonly adopt insights from Kelly's famous work on optimal gambling strategies and the financial value of information. In particular, such models seek evolutionary solutions that maximize long term average growth rate of lineages, even in the face of highly stochastic growth trajectories. Here, we argue for extensive departures from the standard approach to better account for evolutionary contingencies. Crucially, we incorporate considerations of volatility minimization, motivated by interim extinction risk in finite populations, within a finite time horizon approach to growth maximization. We find that a game-theoretic competitive-optimality approach best captures these additional constraints, and derive the equilibria solutions under straightforward fitness payoff functions and extinction risks. We show that for both maximal growth and minimal time relative payoffs the log-optimal strategy is a unique pure-strategy symmetric equilibrium, invariant with evolutionary time horizon and robust to low extinction risks.
