What if physiologists were the only people who study human behavior at all scales: from how the human body functions, to how social norms emerge, to how the stock market functions, to how we create, share, and consume culture?

Source: nautil.us

An elementary cellular automaton with memory is a chain of finite state machines (cells) updating their state simultaneously and by the same rule. Each cell updates its current state depending on current states of its immediate neighbours and a certain number of its own past states. Some cell-state transition rules support gliders, compact patterns of non-quiescent states translating along the chain. We present designs of logical gates, including reversible Fredkin gate and controlled NOT gate, implemented via collisions between gliders.

Logical Gates via Gliders Collisions
Genaro J. Martinez, Andrew Adamatzky, Kenichi Morita

Source: arxiv.org

We studied the long-term dynamics of evolutionary Swarm Chemistry by extending the simulation length ten-fold compared to earlier work and by developing and using a new automated object harvesting method. Both macroscopic dynamics and microscopic object features were characterized and tracked using several measures. Results showed that the evolutionary dynamics tended to settle down into a stable state after the initial transient period, and that the extent of environmental perturbations also affected the evolutionary trends substantially. In the meantime, the automated harvesting method successfully produced a huge collection of spontaneously evolved objects, revealing the system’s autonomous creativity at an unprecedented scale.

 

Seeking Open-Ended Evolution in Swarm Chemistry II: Analyzing Long-Term Dynamics via Automated Object Harvesting
Hiroki Sayama

Source: arxiv.org

Early microbiome research found numerous associations between microbial community patterns and host physiological states. These findings hinted at community-level explanations. “Top-down” experiments, working with whole communities, strengthened these explanatory expectations. Now, “bottom-up” mechanism-seeking approaches are dissecting communities to focus on specific microbes carrying out particular biochemical activities (e.g., choline metabolism pathways, Clostridium difficile suppression). To understand the interplay between methodological and explanatory scales, we examine claims of “dysbiosis,” when host illness is proposed as the consequence of a community state. Our analysis concludes with general observations about how methodologies relate to explanations, and the implications for microbiome research.

 

Methodological Strategies in Microbiome Research and their Explanatory Implications

Maureen A. O’Malley and Derek J. Skillings

Perspectives on Science
Volume 26 | Issue 2 | March-April 2018
p.239-265
https://doi.org/10.1162/POSC_a_00274

Source: www.mitpressjournals.org

Swarms are self-organized dynamical coupled agents which evolve from simple rules of communication. They are ubiquitous in nature, and be- coming more prominent in defense applications. Here we report on a preliminary study of swarm collisions for a swarm model in which each agent is self-propelling but globally communicates with other agents. We generalize previous models by investigating the interacting dynamics when delay is introduced to the communicating agents. One of our major find- ings is that interacting swarms are far less likely to flock cohesively if they are coupled with delay. In addition, parameter ranges based on coupling strength, incidence angle of collision, and delay change dramatically for other swarm interactions which result in flocking, milling, and scattering.

 

The Dynamics of Interacting Swarms
Carl Kolon, Ira B. Schwartz

Source: arxiv.org