Author: cxdig

Self-organisation, (M, R)–systems and enactive cognitive science

Tomasz Korbak

Adaptive Behavior 31(1)

The notion of self-organisation plays a major role in enactive cognitive science. In this paper, I review several formal models of self-organisation that various approaches in modern cognitive science rely upon. I then focus on Rosen’s account of self-organisation as closure to efficient cause and his argument that models of systems closed to efficient cause – (M, R) systems – are uncomputable. Despite being sometimes relied on by enactivists this argument is problematic it rests on assumptions unacceptable for enactivists: that living systems can be modelled as time-invariant and material-independent. I then argue that there exists a simple and philosophically appealing reparametrisation of (M, R)–systems that accounts for the temporal dimensions of life but renders Rosen’s argument invalid.

Read the full article at: journals.sagepub.com

Phase-separation physics underlies new theory for the resilience of patchy ecosystems

Koen Siteur, Quan-Xing Liu, Vivi Rottschäfer, Tjisse van der Heide, Max Rietkerk, Arjen Doelman, Christoffer Boström, and Johan van de Koppel

PNAS 120 (2) e2202683120

Human-induced environmental changes push ecosystems worldwide toward their limits. Therefore, there is a growing need for indicators to assess the resilience of ecosystems against external changes and disturbances. We highlight a novel class of spatial patterns in ecosystems for which resilience indicators are lacking and introduce a new indicator framework for these ecosystems, akin to the physics of phase separation. Our work suggests that aerial imagery can be used to monitor patchy ecosystems and highlights a link between physics and ecosystem resilience.

Read the full article at: www.pnas.org

Economic Complexity Theory and Applications – Cesar Hidalgo

Economic complexity methods have become popular tools in economic geography, international development, and innovation studies. Here, I review economic complexity theory and applications, with a particular focus on two streams of literature: the literature on relatedness, which focuses on the evolution of specialization patterns, and the literature on metrics of economic complexity, which uses dimensionality reduction techniques to create metrics of economic sophistication that are predictive of variations in income, economic growth, emissions, and income inequality.

Watch at: www.youtube.com

Postdoc position on “Creating bio-inspired co-evolutionary incentive systems to promote recycling, using Internet of Things technologies” ETH Zurich

You will produce a simulation program demonstrating self-organizing logistic networks that become more circular and sustainable over time. 

You will create novel research breakthroughs and contribute to the ambitious ERC Advanced Investigator Grant on “Co-Evolving City Life” (CoCi) in subject areas connected to smart cities and digital societies. Your research focus will be on “Sustainable Cities and Coordination”. Given recent digital technologies such as the Internet of Things (sensor and communication networks), Artificial Intelligence, and blockchain technology, one can expect that production, logistics, and even waste, are becoming increasingly smart. Ideally, you will study how the convergence of these technologies can be used to fuel new approaches towards more sustainable production and logistics in an urban context. 

The research question we would like to answer is, how the approach of self-organized and federated, learning, networked multi-agent systems can be used to create socio-economic incentives that would promote the emergence of closed loops in a material supply network and could thereby boost the formation of a circular and sharing economy. We want to study, how a multi-dimensional real-time measurement, feedback and coordination system would have to be designed and operated in order to reach this goal. 

Together with our team, you will work on the mechanisms and effects of multi-dimensional real-time coordination, perform related agent-based simulations, and work towards demonstrating the approach in an application project. It will be great to couple the simulation program with a sensor-based environment (Raspberry Pi or Arduino, or other) that responds to measurements, flexibly adapts, and self-organizes. You will be the key researcher addressing these challenges or a subset of them (please specify), collaborating with a highly motivated team.

More at: www.jobs.ethz.ch

There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-scale Machines

Joshua Bongard, Michael Levin
The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., tendency to oversimplify) and prior technological limitations in favor of a more continuous, gradualist view necessitated by the study of evolution, developmental biology, and intelligent machines. Efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing” – the ability of the same substrate to simultaneously compute different things. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of computational materials as reported in the rapidly-growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of meso-scale events, as it has already done at quantum and relativistic scales. Here, we review examples of biological and technological polycomputing, and develop the idea that overloading of different functions on the same hardware is an important design principle that helps understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.

Read the full article at: arxiv.org