Learning Foraging Thresholds for Lizards: an Analysis of a Simple Learning Algorithm

This paper gives proof of convergence for a learning algorithm that describes how anoles (lizards found in the Caribbean) learnforaging thresholddistance. An anole will pursue a prey if and only if it is within this threshold of the anoleʹs perch. The learning algorithm was proposed by Roughgarden and his colleagues. They experimentally determined that this algorithm quickly converges to the foraging threshold that is predicted by optimal foraging theory. We provide analytic confirmation that the optimal foraging behavior as predicted by Roughgardenʹs model can be attained by a lizard that follows this simple and zoologically plausible rule of thumb.