标题： 随机环境中的最优切换策略 显示英文标题

标题： Optimal switching strategies for navigation in stochastic settings

摘要： 受粪金龟行为中间歇性重新定向策略的启发，我们考虑了在二维空间中运动的活性布朗粒子的导航策略问题。 我们假设，当粒子试图在其固定方向上最大化总位移时，可以通过支付固定成本将其航向重新定向到首选方向。 利用最优控制理论，我们分析推导并数值验证了最大化粒子速度的策略，并表明重新定向之间的平均时间与环境噪声的大小成反比。 然后我们将我们的框架扩展以描述执行误差和感官获取噪声。 我们的方法可能适用于涉及多种感觉模态并需要在自我中心和地理中心策略之间切换的其他导航问题。 显示英文摘要

摘要： Inspired by the intermittent reorientation strategy seen in the behavior of the dung beetle, we consider the problem of the navigation strategy of an active Brownian particle moving in two dimensions. We assume that the heading of the particle can be reoriented to the preferred direction by paying a fixed cost as it tries to maximize its total displacement in a fixed direction. Using optimal control theory, we derive analytically and confirm numerically the strategy that maximizes the particle speed, and show that the average time between reorientations scales inversely with the magnitude of the environmental noise. We then extend our framework to describe execution errors and sensory acquisition noise. Our approach may be amenable to other navigation problems involving multiple sensory modalities that require switching between egocentric and geocentric strategies.