From the Cover: Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework
Year: 2020
Type: article
Abstract: Understanding the movement patterns of wild animals is a fundamental question in ecology with implications for wildlife conservation. It has recently been hypothesized that random search patterns known as Lévy walks are optimal and underlie the observed power law movement patterns of wild foragers. However, as Lévy walk models assume that foragers do not learn from experience, they may not apply generally to cognitive animals. Here, we present a decision-theoretic framework wherein animals attempting to optimally learn from their environments will show near power law-distributed path lengths due to temporal discounting. We then provide experimental support for this framework in human exploration in a controlled laboratory setting and in animals foraging in the wild.
DOI: 10.17615/7rz9-yq79
Authors: Mihalas, Stefan, Namboodiri, Vijay Mohan K., Shuler, Marshall G. Hussain, Levy, Joshua M., Sims, David W.
Institution: University of North Carolina at Chapel Hill
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4301889858