Random searchers cope with cognitive errors and uncertainty better than path planners

There is a widespread belief in ecology that the capacity of animals to orchestrate systematic and planned paths should represent a significant benefit for efficient search and exploration. Within this view, stochasticity observed in real animal trajectories is mostly understood as undesirable noise caused by internal or external effects. Far less is known, however, about the case when cognitive errors and limitations inherent to living systems are explicitly put into play. Here we compare within this context the search efficiency of (i) walkers driven by Bayesian rules generating deterministic paths, (ii) standard random walkers, and (iii) human trajectories obtained from search experiments in a soccer field and on the computer screen. Our results clearly challenge the view that deterministic paths are generally better for exploration than random strategies, as the latter are more resilient to cognitive errors. Instead, we provide numerical and experimental evidence that stochasticity would provide living organisms with a sufficient and cognitively simple exploration solution to the problem of uncertainty.