Amos Korman - An Algorithmic Perspective to Collective Behavior

In this talk, I will present a new interdisciplinary approach that I have been developing in recent years, aiming to build a bridge between the fields of algorithm theory and collective (animal) behavior. Ideally, an algorithmic perspective on biological phenomena can provide a level of fundamental understanding that is difficult to achieve using typical computational tools employed in this area of research (e.g., differential equations or computer simulations). In turn, this fundamental understanding can provide both qualitative and quantitative predictions that can guide biological research in unconventional directions. I will demonstrate this novel approach by presenting a sequence of works on collective ant navigation (published in the biology journals eLife 2016 and eLife 2020, and the CS venues ESA 2018 and TALG 2021), whose experimental part was done in collaboration with the Feinerman ant lab at the Weizmann Institute. In the second part of the talk, I will present a recent result (published in Science Advances 2021) regarding the search efficiency of common animal movement patterns, addressing a long-standing open problem in the area of foraging. I will conclude the talk by discussing potential avenues to employ an algorithmic perspective in biological contexts.