A look at adaptive systems from biology to machine learning
A look at adaptive systems from biology to machine learning lead image
Adaptivity is a key idea in biology, but it’s also found in many other fields, from neuroscience to physics to socioeconomics. Sawicki et al. delve into the various approaches to studying adaptivity, with chapters focusing on applications in machine learning, renewable power grids, music, and more.
Led by Jakub Sawicki, Rico Berner, and Sarah Loos, this article draws on a range of expertise, including from neuroscientists, mathematicians, physicists, computer scientists, and biologists, to provide a comprehensive look at adaptivity as it applies across scientific fields.
Adaptivity has different definitions in various fields; by presenting interdisciplinary summaries, the researchers showcase similarities and differences in focuses and approaches to studying adaptivity. Their goal is to encourage collaboration and improve accessibility for those unfamiliar with technical languages outside their primary fields.
“This article could be used to get an idea of the open questions related to adaptivity existing in various disciplines,” said author Sarah Loos.
“By showcasing the approaches and methods that are already established in various fields, this article can help researchers who look for new methods and possible solutions to tackle the challenges related to adaptivity in their own field,” said author Rico Berner.
For each area, a summary of adaptivity is given, along with its field-specific definitions, methods, and applications. With this breadth of perspectives, the article aims to help highlight all aspects of adaptivity and inspire future work and collaboration between fields.
“This article invites researchers to think in an interdisciplinary manner, and we hope that it will lead to cross-fertilization between the different fields and ideally even to future collaborations,” said author Jakub Sawicki.
Source: “Perspectives on adaptive dynamical systems,” by Jakub Sawicki, Rico Berner, Sarah A. M. Loos, Mehrnaz Anvari, Rolf Bader, Wolfram Barfuss, Nicola Botta, Nuria Brede, Igor Franović, Daniel J. Gauthier, Sebastian Goldt, Aida Hajizadeh, Philipp Hövel, Omer Karin, Philipp Lorenz-Spreen, Christoph Miehl, Jan Mölter, Simona Olmi, Eckehard Schöll, Alireza Seif, Peter A. Tass, Giovanni Volpe, Serhiy Yanchuk, and Jürgen Kurths, Chaos (2023). The article can be accessed at https://doi.org/10.1063/5.0147231 .
